Dialpad’s “Agentic AI” Vision and New Enterprise Contact Center Features
Dialpad’s latest announcements signal an ambitious push toward AI-driven customer service, introducing a vision of “Agentic AI” for pre-emptive support and a suite of new features.
Executive Summary
Dialpad’s latest announcements signal an ambitious push toward AI-driven customer service, introducing a vision of “Agentic AI” for pre-emptive support and a suite of new enterprise contact center features. In summary, Dialpad is positioning itself at the forefront of AI in the contact center by outlining a future where AI autonomously anticipates and resolves customer needs before issues arise. At the same time, the company is rolling out practical enhancements – from real-time agent coaching to AI-generated CSAT scoring – aimed at delivering immediate value to enterprise contact centers. This briefing evaluates these announcements with a balanced lens, acknowledging the innovation while discussing the gap between launching a “vision” and delivering proven outcomes. We also benchmark Dialpad’s strategy against EndeavorCX’s Vitalogy (considered a gold standard in the industry) to assess how Dialpad’s offerings stack up in the current competitive landscape.
Key Takeaways:
Agentic AI Vision: Dialpad’s vision of pre-emptive, autonomous customer service (Agentic AI) aligns with industry trends but remains largely aspirational until the promised platform is delivered in late 2025. There’s a clear difference between announcing this future capability and having it in production, and we remain cautiously optimistic.
New Features for Enterprises: Dialpad’s new features – including real-time AI coaching, AI-based CSAT (“aiCSAT”) scoring, deeper CRM integrations, workforce management tools, and improved Microsoft Teams integration – enhance its platform’s enterprise readiness. These updates address many core needs of contact center operators, though none are wholly revolutionary by market standards.
aiCSAT and AI Coaching: Dialpad’s aiCSAT feature can automatically generate a customer satisfaction score for every call along with insights into what drove that outcome. This is a notable step towards data-driven quality management, but its strategic value will depend on accuracy and acceptance relative to traditional CSAT methods. Real-time AI coaching (Ai Live Coach) continues to be a strength, now extending to more scenarios (like meetings) to proactively guide agents with knowledge and next-best responses in the moment.
Competitive Benchmark (EndeavorCX’s Vitalogy): EndeavorCX’s Vitalogy AI platform represents a cutting-edge, AI-first approach to customer experience, with a unified semantic engine that delivers deep, real-time insights and orchestrates actions across channels. Compared to Vitalogy’s open, vendor-agnostic intelligence core, Dialpad’s AI capabilities are more integrated into its own CCaaS platform – powerful for Dialpad users, but less flexible in heterogeneous environments. Vitalogy’s emphasis on context, real-time “CX vitals,” and multi-channel intelligence sets a high bar that Dialpad will need to meet as it evolves its Agentic AI vision.
Product Readiness & Alignment: Many of Dialpad’s newly announced features are available now or imminently, bolstering its platform for enterprise use (e.g. advanced analytics, WFM adherence, security controls). In contrast, the fully autonomous Agentic AI capabilities are not due until Fall 2025, highlighting a gap between vision and current product. Enterprises evaluating Dialpad should weigh the immediate benefits of the new features against the longer wait for the more transformative AI functions. Dialpad’s roadmap aligns well with enterprise trends (proactive service, AI augmentation, integration with existing tools), but achieving true “pre-emptive customer service” at scale remains a challenging, unproven endeavor.
Gaps & Market Outlook: We identify some gaps – notably the reliance on future promises (Agentic AI) and the potential closed-loop nature of Dialpad’s AI vs. more open ecosystems – as well as opportunities for Dialpad to differentiate if it delivers on its claims. Initial market reaction is likely to be mixed: cautious optimism from Dialpad customers and industry watchers, but also skepticism from decision-makers who have seen similar AI hype cycles. Competitors (including the likes of EndeavorCX, as well as incumbents like Genesys or NICE) will undoubtedly scrutinize Dialpad’s “vision” and emphasize their own proven AI capabilities. Ultimately, Dialpad’s credibility in the enterprise contact center segment will hinge on turning this Agentic AI vision into tangible outcomes and referenceable successes.
Introduction and Background
The contact center industry is in the midst of an AI-driven transformation. Recent Gartner research predicts that by 2029, “agentic AI” systems will autonomously handle 80% of standard customer service queries, potentially cutting operational costs by 30%. Agentic AI refers to advanced autonomous AI that doesn’t just assist humans, but can take independent action to resolve customer requests. In this context, vendors are racing to infuse AI into customer service platforms, promising everything from smarter analytics to conversational agents that proactively address issues.
It’s against this backdrop that Dialpad, Inc., a cloud contact center and unified communications provider, made two significant announcements in May 2025:
A strategic vision for “Agentic AI” – Dialpad’s blueprint for enabling pre-emptive customer service in which AI anticipates and addresses customer needs before they become problems. This vision was laid out in a press release detailing how Dialpad plans to evolve its platform towards greater autonomy and intelligence in customer interactions.
A set of new features and updates for the enterprise contact center – revealed on Dialpad’s blog – that deliver immediate enhancements to its current product. These include AI-powered features (like an AI-generated CSAT metric and expanded real-time coaching), deeper integrations (CRM and Microsoft Teams), improved workforce management, multi-language support, and even a company brand refresh.
Combined, these announcements paint a picture of Dialpad’s strategy: deliver useful tools now, while staking a claim in the AI future of customer service. This briefing will dissect both elements of Dialpad’s news, examining the substance behind the vision and features. We will also provide a comparative analysis with EndeavorCX’s Vitalogy, a new CX intelligence platform that many analysts view as a benchmark for AI excellence in contact centers. The goal is to help contact center decision-makers separate hype from reality and understand the practical implications of Dialpad’s moves for their operations.
Dialpad’s “Agentic AI” Vision for Pre-Emptive Customer Service
Dialpad’s press release trumpets a bold vision of an Agentic AI platform that will enable pre-emptive customer service. In Dialpad’s words, this means “anticipating and addressing customer needs before they become issues”, through autonomous systems that adapt in real time, execute complex tasks with minimal human oversight, and ensure seamless AI-to-human handoffs. Essentially, Dialpad is aligning with the industry’s aspiration for AI-driven service that moves from reactive to proactive.
Key components of the Agentic AI vision include:
Fully Autonomous AI Agents: Dialpad describes future AI agents that can handle end-to-end tasks such as order tracking, appointment management, and initial HR screening without human intervention. For example, an AI agent could automatically authenticate a customer, pull up order information, and provide real-time shipping updates or reschedule an appointment by interfacing with back-end systems. These are tasks typically requiring an agent’s time; automating them could greatly reduce handle times and improve customer convenience.
Real-Time Adaptation and Complex Task Completion: The vision emphasizes AI systems that adapt in real time and complete complex tasks. This implies a level of AI sophistication beyond simple chatbots or IVRs – something closer to an AI workflow engine that can interpret context, make decisions, and act (for instance, negotiating a solution or triggering a process) during a customer interaction. Dialpad’s CEO, Craig Walker, frames this as “revolutionizing customer interactions” with systems that push boundaries and empower businesses in new ways.
Seamless AI-Human Handoffs: Recognizing that AI won’t handle 100% of interactions, Dialpad highlights ensuring smooth transitions between AI and human agents. In practice, this means if an AI agent reaches its limit or the customer requests a human, the context is transferred so the live agent can pick up without missing a beat. This is crucial for customer experience – a failed handoff can be worse than no AI at all. Dialpad’s vision suggests this coordination is a core design goal of their Agentic AI platform.
Agentic Platform & Toolkit: Dialpad mentions an “agent management toolkit” aimed at speeding up and simplifying the deployment of these AI capabilities by up to 75%. While details are sparse, this implies there will be tools for businesses to configure, train, and monitor their AI agents (for example, defining workflows the AI should handle, integrating knowledge bases, setting thresholds for escalation, etc.). Enterprise IT and operations teams will need such controls to implement AI agents effectively.
According to Dialpad, this Agentic AI platform is slated for availability in Fall 2025, with early access for select customers and partners sooner. This timeline is important – it signals that, as of mid-2025, much of this vision is still in development. Dialpad is essentially pre-announcing what’s coming, likely to reassure customers and market watchers that it’s staying ahead of the curve. The company touts its current unique position as “the only contact center platform that can coach live agents in real time using native AI” – a capability it has today – and says it will “soon augment those solutions with fully agentic AI”. The implication is that Dialpad believes it has a head start on AI (with its in-call coaching features) and will build on that to achieve autonomous customer service.
However, it’s worth noting here: Announcing a visionary roadmap is far easier than delivering it. The press release’s confident language (“Dialpad is uniquely positioned to lead the market in agentic AI”) must be weighed against the reality that no vendor has fully cracked pre-emptive, autonomous service at scale yet. Gartner’s forecast of agentic AI solving 80% of issues by 2029 underscores that we’re still in the early innings of this journey. If Dialpad succeeds, it could indeed transform how businesses serve customers; but until the promised platform is in customers’ hands demonstrating results, Agentic AI remains more vision than proven product. Competitors are also pursuing similar goals – for instance, Salesforce’s newly introduced “Agentforce” and other CCaaS leaders are integrating generative AI to handle customer intents – so Dialpad will need to execute exceptionally to make this vision a differentiator and not just marketing parity.
In summary, Dialpad’s Agentic AI vision is ambitious and on-trend. It paints a future of contact center operations with dramatically lower customer effort and higher automation, aligning with the industry’s direction towards proactive service. Yet, the path from vision to reality is fraught with challenges: training AI to truly understand nuanced customer requests, integrating with myriad enterprise systems securely, handling exceptions, and building trust in machine-driven service. Dialpad has set Fall 2025 as its target to unveil this future, giving it roughly 12-18 months from announcement to delivery. The next year will be critical for Dialpad to prove that Agentic AI is more than aspirational hype – perhaps via pilot programs, beta customer testimonials, or incremental releases that showcase pieces of this autonomous functionality in action.
New Enterprise Contact Center Features and Updates
Complementing its forward-looking vision, Dialpad also announced a range of immediate product enhancements squarely aimed at enterprise contact center needs. These features, detailed in a recent Dialpad blog post, suggest that while the company works toward the Agentic AI future, it is also bolstering its current platform to be more powerful, user-friendly, and enterprise-ready. Below we break down the major updates:
Real-Time AI Coaching (Ai Live Coach) Enhancements: Dialpad’s real-time agent coaching, which uses AI to provide live guidance during calls, is a flagship feature of its platform. It’s described as “proactive, in-the-moment guidance for live agents during each and every conversation, including real-time information gathering from the company’s entire knowledge base.” This means as agents talk to customers, Dialpad’s AI can pop up suggestions, answers, or even warnings if, say, an agent is veering off-script or missing a policy detail. Dialpad reports that this AI Live Coach was already a “hit in support” scenarios and now has been extended to work in other contexts like internal meetings. In practice, this turns the common phrase “Let me find out for you” into a faster “Here’s what you need to know,” assisted by real-time knowledge base lookups. By expanding AI coaching to more use cases, Dialpad is doubling down on the idea of AI as a co-pilot for agents – an area where it arguably leads, though competitors (e.g. Five9’s Agent Assist or Genesys’s Agent Assist) offer similar functionalities with their own AI or partnerships.
aiCSAT (AI Customer Satisfaction Scoring): Perhaps the most notable new feature is what Dialpad calls Ai CSAT (sometimes stylized as “Ai CSATx”). This capability automatically generates a CSAT score for every call using AI, and – critically – provides insights into the factors that influenced that score. Essentially, Dialpad’s AI analyzes the conversation (tone, sentiment, keywords, outcomes) and produces an estimated customer satisfaction rating at the end of the call, along with context such as what went well or poorly. For example, it might flag that a customer sounded frustrated about long hold times or was pleased with a prompt resolution, thus explaining a low or high CSAT prediction. Dialpad says Ai CSAT delivers CSAT scores “for all calls” and “amplifies that information with actionable insights about the factors that influenced them.” This feature addresses a pain point in customer experience management: traditionally, CSAT is measured via post-call surveys, which only a fraction of customers respond to. An AI-based score could give managers 100% coverage of interactions. That said, its accuracy versus actual survey responses will be something to watch – it’s a bold move to equate AI inference to a metric as important as CSAT. (We’ll discuss critical commentary on aiCSAT in a dedicated section later in this briefing.)
Expanded Integrations and Data Access: Recognizing that agents need full context to serve customers, Dialpad has added more customer data integrations into its platform. The press release highlights expanded integrations with CRMs and other systems like Salesforce, HubSpot, Freshdesk, Microsoft Teams, and more, enabling agents to see relevant customer info and history during calls. Additionally, Dialpad now automatically syncs call summaries, action items, transcripts, and dispositions into CRM systems within minutes after a call. This streamlines a lot of post-call admin work (no more copy-pasting notes to Salesforce manually) and ensures a single source of truth in the CRM. For enterprises, these types of integrations are crucial – they reduce friction in workflows and improve data consistency. Dialpad enhancing them indicates a maturing product focused on fitting into customers’ existing tech stacks rather than being a standalone silo.
Workforce Management (WFM) and Agent Management Tools: New workforce management adherence reporting is introduced, giving leaders insight into how agents’ time is spent versus their schedules. Adherence to schedule is a classic contact center KPI (important for staffing and operational efficiency), so Dialpad adding this shows it is serious about core contact center operations. Additionally, Dialpad’s “Optimize” tab in the AI Agent toolkit now provides managers with guidance to improve AI agent accuracy and increase deflection rates. This indicates Dialpad has (or is developing) a toolkit for managing digital agents or chatbots, and it’s refining that with better analytics – likely in preparation for the more autonomous Agentic AI to come. It’s worth noting that Dialpad is thinking of managers not just as coaches for human agents, but also as “coaches” or tuners of digital agents, which is a forward-looking approach as AI agents become part of the workforce.
Omnichannel Quality and Accountability: The platform updates include digital dispositions and scorecards for non-voice interactions (chat, email, etc.). This brings the same level of accountability and performance tracking to digital channels as voice calls. Managers can now track and rate interactions over chat or email similar to calls, ensuring quality standards across all channels. This is an important feature for enterprises that engage customers on multiple channels – consistent metrics and the ability to monitor interactions regardless of medium are key to a unified customer experience.
Deeper Microsoft Teams Integration: Many large enterprises use Microsoft Teams for internal collaboration; Dialpad is catering to those by making it easier to integrate Dialpad Contact Center with Teams. The updates include presence syncing (so agent status is aligned between Dialpad and Teams), a cleaner embedded app experience within Teams, and simpler direct routing setup. Essentially, Dialpad can function as the contact center voice solution while Teams remains the user interface for employees – with these improvements, users can click to dial, see statuses, and manage calls from Teams directly, while leveraging Dialpad’s AI features in the background. Dialpad is also aiming for official Microsoft certification as a contact center solution by this fall, which would boost credibility for Microsoft-centric shops. This focus on Teams integration shows Dialpad’s strategic awareness: to win enterprise customers, you need to play nicely with the platforms they’ve already standardized on.
Globalization (Language Support) and Scalability: Dialpad has expanded its AI language support to eight languages – explicitly English, Spanish, French, German, Italian, Japanese, and more. This is vital for global enterprises that operate multilingual contact centers. It means Dialpad’s real-time transcription, coaching, and analytics can function in those languages, not just English. They also announced the ability to host large meetings with up to 1,500 participants, added breakout rooms, and a hardware-optimized room solution via a partnership with Neat (a video conferencing hardware vendor). While the meetings capability is a bit tangential to contact centers, it indicates Dialpad’s unified communications side is scaling up – useful for companies that want one vendor for both UC and CC.
Security and Admin Improvements: On the IT side, Dialpad is integrating with Microsoft Intune for mobile device management and added more granular role-based access control (RBAC) with predefined permission sets. Enterprises will appreciate these, as they make it easier to enforce security policies on employee devices and delegate admin rights safely. Data governance and compliance tools were also mentioned in the press release, though details are sparse – likely things like data retention settings, audit logs, and compliance certifications which enterprises often require.
User Experience Tweaks (“Sweating the Details”): Dialpad has made a series of quality-of-life improvements to its agent and supervisor interface. These include better chat usability (inline replies, swipe through unread mobile messages, translate messages in-app, sorting channels, message reminders). While minor individually, these enhancements remove daily friction and show that Dialpad is listening to user feedback on the little things. A refreshed user interface and brand with a modernized logo and color palette also debuted. The UI refresh isn’t just cosmetic; Dialpad claims it brings “ease of use enhancements” that reflect their philosophy of making AI tools “powerful [yet] easy-to-use”. A cleaner, more intuitive interface can drive adoption – an important factor for enterprise rollouts.
Collectively, these updates indicate that Dialpad is addressing the fundamentals that enterprise contact centers care about: agent performance, customer satisfaction measurement, omnichannel engagement, integration with enterprise IT ecosystems, security/compliance, and scalability. None of these features is entirely unique in the market – for instance, most leading CCaaS platforms offer CRM integrations, WFM capabilities, and Teams connectivity either natively or via partners. However, the fact that Dialpad is building them into its platform shows a commitment to being an all-in-one solution. It’s moving from a challenger with cool AI features to a more well-rounded enterprise platform.
One could say these announcements also serve to fill gaps Dialpad had compared to larger competitors. For example, traditional contact center suites (Avaya, Cisco, Genesys) have long had workforce management and adherence reporting, deep telephony integration, etc. Dialpad’s need to highlight WFM adherence and RBAC now suggests those were areas where it needed improvement to be taken seriously for large deployments. The same goes for omnichannel quality tools – a mature contact center should manage voice and digital channels uniformly, and Dialpad is catching up on that front with digital scorecards. This is not to downplay the importance of the features – rather, it’s to note that Dialpad is in a race to check all the enterprise boxes while still pushing its AI differentiation.
In conclusion, the new features and updates give Dialpad customers tangible tools to use today. They provide a more solid foundation on which the grand Agentic AI vision can later stand. For an enterprise evaluating Dialpad, these enhancements make the platform more credible: AI that not only dreams big (autonomous agents someday) but also delivers now (better coaching, insights, and integration today). The next sections will examine in more detail two critical aspects: the aiCSAT capability and how all of this compares to what competitors like EndeavorCX are doing, especially regarding proven AI outcomes.
The aiCSAT Factor: AI-Driven Customer Satisfaction Scoring in Context
One of the most intriguing (and potentially controversial) features in Dialpad’s arsenal is aiCSAT – the AI-generated customer satisfaction score. In concept, aiCSAT aims to automatically assess how satisfied a customer likely is at the end of a call, without requiring the customer to fill out a survey. Dialpad not only assigns a score but also identifies the drivers of that satisfaction level, providing “actionable insights about the factors that influenced [the score]”.
Capabilities and Potential: From an operational standpoint, aiCSAT could be quite powerful. Managers and quality analysts get immediate feedback on every interaction. For example, if a call went poorly, aiCSAT might highlight that the customer had to repeat information multiple times or sensed agent uncertainty – valuable clues for coaching. Over time, patterns from aiCSAT could identify common pain points (e.g., a particular policy always upsets customers, or calls over a certain length tend to lead to low satisfaction). This kind of insight traditionally required manually listening to calls or waiting for survey responses, so automating it can significantly accelerate the feedback loop. Moreover, because aiCSAT presumably scores all calls, it shines light on the vast majority of interactions that never get a survey response. It can effectively serve as an “early warning system” – if many calls are scoring poorly via AI, something may be brewing (a product issue, a knowledge gap, etc.) that needs attention before official CSAT surveys or NPS scores catch up.
Dialpad is not the first to try something like this. Market standards for AI-driven sentiment or satisfaction analysis exist in various forms. Competitors like NICE and Verint have AI sentiment analysis models (NICE Enlighten, for instance, can predict customer sentiment and even outcome metrics). Other CCaaS platforms have experimented with predictive NPS or real-time sentiment scoring based on speech analytics. So aiCSAT is in line with an industry trend to go beyond just transcribing calls to actually interpreting customer emotion and satisfaction. What Dialpad appears to be doing is packaging it in a way that directly mirrors a key metric (CSAT) that businesses already track religiously. That framing is strategic: rather than just saying “we analyze sentiment,” tying it to CSAT gives executives a familiar yardstick.
Critical Perspective: Despite its promise, aiCSAT should be met with some healthy skepticism until proven. How accurate is it? The reliability of an AI-predicted satisfaction score likely hinges on training data. If Dialpad trained the model on large datasets of calls where they know the real CSAT (from surveys) or resolution outcomes, the AI can learn patterns. But customer satisfaction is subjective and culturally influenced – tone of voice, choice of words, even the customer’s personality can affect it. There’s a risk of false positives/negatives: e.g., a polite customer might not express anger vocally, yet still be dissatisfied (AI could misread it as a neutral call when in fact the customer won’t buy again). Or an irate tone might be just a personality trait and the customer is actually satisfied by the end, but the AI latches onto the negativity. Dialpad will need to continuously refine aiCSAT and likely allow clients to calibrate it to their environment (one hopes there’s a feedback mechanism, such as confirming AI scores against real survey responses when available, to improve the model).
Furthermore, strategic weight relative to market standards should be considered. Actual CSAT (via surveys) remains the gold standard metric for customer happiness. It’s often tied to bonuses, SLAs, and strategic decisions. It’s unlikely enterprises will abandon real surveys just because an AI gives a score. Instead, aiCSAT will probably be used as an adjunct – a fast internal indicator. At least initially, many organizations might treat it as a form of augmented sentiment analysis rather than a definitive measure. Over time, if Dialpad can demonstrate that aiCSAT has a high correlation to real CSAT and business outcomes, it could carry more weight. But trust won’t be built overnight. In the interim, aiCSAT could face scrutiny from operations and CX leaders: does a high aiCSAT truly mean customers are happy, and vice versa? Savvy decision-makers will demand validation. They’ll also compare it to what others offer. If EndeavorCX’s Vitalogy or other analytics tools provide similar sentiment/quality scoring (even if not labeled “CSAT”), the differentiation might blur.
It’s also worth noting the naming (“CSAT”) might set expectations. CSAT is usually measured as a percentage of respondents who are satisfied (often those giving a top-2-box rating on a survey). Dialpad’s aiCSAT might output a score per call (perhaps 0-100 or 1-5 scale, etc.). How that rolls up into a familiar CSAT percentage is unclear. There’s some marketing flair here in calling it CSAT – it grabs attention more than “AI sentiment score.” The slight cynic might say it’s a rebranding of sentiment analysis with a CX twist. But if the delivered insights truly map to drivers of satisfaction, it could be more valuable than generic sentiment alone. For example, identifying that “agent product knowledge” or “hold time” was the key dissatisfier in a call is actionable information.
Strategic Weight: In the broader market, an automated CSAT scoring capability is a nice-to-have feature, but not a game-changer on its own. Many contact center decision-makers are currently more excited by AI that can either drive revenue (through personalization, next-best-offer) or cut costs (through automation). AiCSAT sits in the quality monitoring realm – important for continuous improvement, but a step removed from directly improving the bottom line. That said, ensuring quality and customer happiness is crucial for retention and brand reputation, so it isn’t trivial. It’s just that aiCSAT is likely to be one feature among many that an enterprise considers. Its strategic value will increase if Dialpad can demonstrate that using aiCSAT leads to better coaching and thus higher actual CSAT over time.
In conclusion, aiCSAT is an innovative feature that shows Dialpad’s AI prowess, but it will require vetting in real-world use. We will be watching to see early adopters’ feedback: Do supervisors find the AI insights accurate and helpful? Does it reduce reliance on after-call surveys? Does it improve agent behavior (e.g., if agents know every call is “scored,” do they try harder to delight customers)? There’s potential for aiCSAT to differentiate Dialpad if done well, as not all competitors offer a comparable built-in metric. However, if done poorly or over-sold, it could become a cautionary tale (the last thing Dialpad needs is customers complaining that “the AI said our CSAT is great, but we’re actually getting complaints”). For now, we view aiCSAT as a valuable addition with a lot of promise, one that needs to be empirically proven and likely fine-tuned in partnership with clients as they deploy it.
Vision vs. Reality: From Hype to Product – An Execution Perspective
One theme threading through Dialpad’s announcements is the tension between visionary marketing and tangible product reality. As industry analysts, we often see vendors announce grand plans (especially involving AI) that sound impressive but take time – sometimes years – to materialize, if they ever do. Dialpad’s “Agentic AI” falls squarely into that category: a bold proclamation of where the platform is headed, presumably intended to position Dialpad as an innovator and keep customers excited (and maybe pause them from looking at competitors). The question is, how well can Dialpad execute to turn this vision into mature, proven outcomes?
From an outside viewpoint, one could say “Dialpad is selling futures” here. The fully autonomous AI scenarios (order tracking bots, AI scheduling agents, etc.) are conceptual prototypes at this stage. They won’t be generally available until late 2025, and even then, likely in an evolving state. History has shown that early versions of such AI solutions can be limited or brittle. For instance, many companies rolled out chatbots in the late 2010s with high hopes, only to find they could handle 10-20% of inquiries and often frustrated customers – leading to a retrenchment and more realistic approaches. Today’s AI is certainly far more advanced (especially with the advent of large language models and better conversational AI), but fully trusting complex tasks to AI agents is still frontier territory. We have to consider operational challenges: integration with legacy systems (the AI needs to access order databases, scheduling tools, etc.), maintaining security (autonomous actions require permissions and audit trails), and handling the unpredictable nature of real customer queries.
Dialpad does have a track record of delivering AI features (its real-time transcription and coaching have been in use for a while). They cite a Forrester Total Economic Impact study showing quantifiable improvements like a 20% reduction in average handle time and 50% decrease in post-call work for customers using Dialpad’s real-time AI. Those are mature, proven product outcomes from the current platform – evidence that Dialpad’s AI can drive efficiency. This gives Dialpad some credibility that it can create useful AI tools. The jump from assisting agents to replacing tasks entirely, however, is a significant one.
Crucially, Dialpad’s press release itself draws a line between what’s available now and what’s coming. The immediate enhancements (like AI live coach improvements, aiCSAT, integrations) are positioned as delivering “immediate business value” – presumably because they are in-market or soon to be. In contrast, the Agentic AI platform is future (“will be available in fall 2025”). This bifurcation is wise: it sets customer expectations that today you get X, tomorrow you might get Y. But it also invites the scrutiny of how much of the vision is vaporware at present.
One might ask: Why announce the Agentic AI vision now, rather than waiting until the product is closer to ready? Common reasons could be: to assert thought leadership (so Dialpad is seen as leading the conversation on pre-emptive AI service, not lagging); to counter competitors’ AI narratives by saying “we have something bigger coming”; or to attract investor and media attention as an AI-driven company. The risk is if the market perceives a large gap between talk and substance. For enterprise buyers, a flashy vision might be interesting, but they will base purchase decisions on capabilities they can actually use and trust. Dialpad’s slight repositioning (with brand refresh, etc.) looks like it’s aiming to move upmarket – but big enterprises can be the most skeptical audience for unproven tech. They often pilot new features extensively before full rollout, and they expect references or case studies.
Comparatively, what’s the track record in the industry? Looking at others: Genesys, for example, has been talking about AI in customer experience (“Autonomous CX” concept) and rolling out pieces like predictive routing and AI-based conversational IVR. But even Genesys hasn’t proclaimed a near-term fully autonomous contact center – their approach is more incremental (blend AI with humans gradually). Smaller innovative firms like Amelia (IPsoft) have long promised human-like AI agents, with some success in narrow domains but not wholesale replacement of contact center agents. The point is, Dialpad is certainly not alone in the vision, but the execution will set it apart. If by end of 2025 Dialpad can showcase real clients using AI to, say, deflect a significant chunk of calls with those autonomous agents, it will have delivered on something many have strived for.
Real-time coaching uniqueness claim: Dialpad repeatedly notes it is “the only contact center platform that can coach agents in real time with native AI”. This sounds like a bit of marketing hyperbole. While Dialpad’s native AI capabilities are indeed a strength, competitors do have real-time agent assist features (though sometimes via add-ons or integrations). For instance, Cisco’s Webex Contact Center has real-time sentiment and guidance, Five9 partners with companies like Cogito for real-time emotional AI coaching, and NICE has real-time compliance checks with Enlighten. Perhaps Dialpad’s angle is that it’s all built in-house (native) rather than via third-party. That is a valid point – owning the tech stack can mean faster improvements and more seamless integration. But by claiming sole leadership, Dialpad invites competitors to challenge that narrative. An analyst or savvy customer might view such absolute claims with a raised eyebrow. It doesn’t detract from Dialpad’s capability, but it underscores that we should be cautious about vendor “first and only” assertions in a fast-moving market.
Execution Challenges: Delivering the Agentic AI vision will require Dialpad to solve several technical and operational challenges:
AI Model Accuracy and Control: Autonomous CX requires very accurate natural language understanding and dialog management. Dialpad will need top-notch AI models (possibly leveraging large language models, but with guardrails) that can handle complex requests and know when to escalate to humans. There’s also the matter of control – enterprises will demand the ability to configure what the AI can and cannot do, and to define business rules. Building a flexible but safe framework for AI autonomy is non-trivial.
Integration and Ecosystem: For AI to take actions (like updating an order or scheduling an appointment), Dialpad must integrate deeply with various enterprise systems (ERP, CRM, scheduling software, etc.). This could mean a lot of partnership or API work. EndeavorCX’s approach (as we’ll discuss) is very integration-centric (API-first). Dialpad, as a CCaaS, historically integrates with CRMs and a few systems but will have to broaden that significantly to fulfill all the use cases of Agentic AI.
Testing and Fail-safes: In customer service, an error by an AI can be costly (think: AI cancels the wrong order, or gives a customer incorrect information). Dialpad must implement extensive testing, likely using human-in-the-loop oversight at first. Perhaps Agentic AI will start with narrow tasks in controlled pilots. The fall 2025 GA target suggests 2025 is for development and closed testing; one hopes by launch they have solid evidence from beta clients that it works as intended.
Change Management for Customers: Even if Dialpad builds it, will enterprises use it fully? Adopting autonomous AI in customer ops is as much a change management issue as a tech issue. Companies will need to train their staff to supervise AI agents, adjust KPIs (how do you measure an AI agent’s performance?), and handle workforce impacts (could AI reduce headcount or change roles?). Dialpad as a vendor will need to guide customers through that transformation. If they oversell and under-support, clients might enable the flashy AI features and then disable them after a bad incident. So execution includes customer success and support to realize the value.
In fairness, Dialpad appears mindful of some of these issues – offering the agentic toolkit for implementation efficiency, emphasizing seamless handoffs, and highlighting its successes with current AI features to build confidence. But the proof will be in the pudding. At this stage, Dialpad has planted a flag in the future, but the path to reach it is under construction. The risk is competitors or newcomers could reach that flag first or cast doubt on Dialpad’s ability to get there. The opportunity is Dialpad could define the narrative and be seen as a visionary leader if it delivers.
For decision-makers, the prudent approach is to appreciate Dialpad’s vision but not be swept up by hype. In RFPs and discussions, ask Dialpad tough questions: Can you demonstrate a working prototype of these autonomous agents? What early results can you share? What happens if the AI fails – how does the system detect and recover? Also inquire about the roadmap in detail – is Fall 2025 for a beta or a full release, and what features exactly will “Agentic AI platform” entail at first launch? The answers will reveal how far along they truly are. Meanwhile, focus on the improvements that are here now (like aiCSAT, etc.) as indicators of the company’s innovation capability and use those to gauge how well Dialpad executes on promises in the shorter term.
Product Readiness, Technical and Operational Implications, and Enterprise Alignment
When evaluating Dialpad’s announcements, it’s crucial to assess how ready the products are, what technical or operational considerations they entail, and how well they align with enterprise contact center needs. We’ve touched on many of these aspects, but let’s consolidate the analysis:
Product Readiness: On one hand, Dialpad’s new enterprise features (AI coach, aiCSAT, integrations, WFM tools, etc.) are either already available or rolling out now. This means enterprise customers can immediately benefit from them. For example, AI-powered live coaching is already in use (with customer testimonials like Foley’s VP citing saved supervisor hours through AI guides), and the improved integrations and dashboards are part of the current platform. This indicates a level of maturity in Dialpad’s core offering – it’s not all vaporware; there are concrete capabilities with proven value (reinforced by the Forrester TEI study results of efficiency gains). Dialpad’s platform has been evolving for years (including acquisitions of TalkIQ for AI), so features like transcription, sentiment analysis, etc., are fairly robust by now. The additions like WFM adherence or better chat UX are incremental and should be straightforward.
On the other hand, the Agentic AI elements (autonomous agents) are not ready until late 2025. That means any use cases dependent on those (like fully automated order tracking via AI agent) are in planning/pilot stage at best. For an enterprise making decisions in mid-2025, one would consider these as roadmap items – something to maybe beta test late in the year or in 2026 planning, but not bank on for immediate operation. Therefore, Dialpad’s current product readiness is strong on AI-assisted human agents, weak on AI-only agents (for now). The good news is customers can adopt the available pieces (AI assist, aiCSAT) and simultaneously prepare for the autonomous features when they arrive, rather than having to wait with no benefit.
Technical Implications: Deploying Dialpad’s new features requires some technical integration and oversight:
Integrations: Companies will need to connect Dialpad with their CRMs (Salesforce, HubSpot, etc.) and other systems to fully leverage the new data syncing and knowledge base features. This is a typical implementation task; Dialpad’s expanded native integrations should ease the load, but IT teams should plan for testing data flow (e.g., ensuring call transcript data properly lands in Salesforce records). The deeper Teams integration is a boon technically (less custom work for those environments), but it does mean one more system (Teams) to keep configured correctly with Dialpad.
AI Training and Tuning: For features like Ai Live Coach and aiCSAT, some training or tuning might be needed. Ai Live Coach uses a library of prompts and playbooks (Foley created an “extensive AI Live Coach library” for their compliance guides), which means someone in the organization curates and maintains the real-time coaching tips. That is a new operational task, possibly for a knowledge manager or QA lead. It’s technical in the sense of using Dialpad’s interface to input content and keywords that trigger tips. AiCSAT might need calibration – initially one might run it in the background to compare with real survey scores, then decide threshold of what AI CSAT score is considered “good” or “bad” in their context. It’s somewhat plug-and-play, but smart users will treat it as a model that can improve with feedback.
Security & Compliance: Introducing AI and new integrations raises questions of data security. Transcripts, for instance, may contain sensitive info. Dialpad’s improved security controls (and the Trust Center) need to be vetted against enterprise requirements. Features like remote desktop control (mentioned as a new feature for agents) also require security scrutiny – how is access managed, logged, etc. Enterprises in regulated industries will want to know how Dialpad’s AI complies with privacy (e.g., if aiCSAT analyses call content, does it store recordings, and for how long? Can it avoid analyzing PCI or HIPAA sensitive segments?). These are technical considerations that the IT security team must evaluate. Dialpad seems aware, offering things like data governance tools, but the specifics matter (e.g., is data encryption end-to-end, can models be hosted in-region for data residency, etc.).
Operational Implications: The introduction of these AI capabilities will impact various roles and processes in the contact center:
Agent Workflow: Agents using Dialpad will increasingly have AI at their side. With real-time coach, they’ll see prompts during calls. This requires training agents to not be distracted or offended by AI coaching, but to incorporate it. The best results come when agents trust the AI suggestions. If aiCSAT is visible to agents or used in performance reviews, it could alter behavior (good if it motivates better service, bad if it causes agents to “game” the system or stress over an AI’s judgment). Supervisors will need to set the tone that these tools are there to help, not punish. Also, features like automated disposition or CRM logging mean agents do less after-call work; that’s a positive, but managers might then raise productivity targets (i.e., if wrap-up is auto, maybe you can take more calls per hour). So workforce planning may adjust expectations accordingly.
Supervisor and QA Workflow: Supervisors get more real-time data (aiCSAT scores, alerts from AI coach). They might shift from random call review to targeted coaching: for example, focusing on calls where aiCSAT was low or where the AI flagged a compliance issue. This makes their job more efficient, but also requires analytical skills – interpreting AI insights and deciding on actions. The “Optimize” tools for AI agents suggest that if a company uses chatbots or IVRs, the contact center team now also oversees the “digital workforce.” That’s a new operational element: monitoring AI agent deflection rates and accuracy, almost like managing another shift of agents (just bots instead of humans). Some companies create an AI operations team for this; others fold it into existing QA teams.
Capacity and Routing: If and when the Agentic AI autonomous features go live, contact volume handling could change. Routine tasks might be deflected entirely to AI. That means human agents handle proportionally more complex issues. Training and hiring profiles might shift towards more skilled problem-solvers, as simple inquiries no longer reach them. Schedules might also change – perhaps fewer agents needed at certain times if AI handles common queries 24/7. However, AI may introduce new categories of work, like reviewing AI-handled cases or stepping in when AI transfers a call. In other words, operations managers will need to redesign call flows and workforce planning once AI agents are in play. Initially, they might run AI in a limited capacity (e.g., only on a specific queue) and gradually expand as confidence grows.
Customer Experience Management: If Dialpad’s vision holds, customers may start interacting with AI first more often (pre-emptive service). Companies should plan how to communicate this to customers. Will customers know they are chatting with an AI? Dialpad’s success will partly depend on those AI interactions being smooth; otherwise, agents may get more annoyed customers who tried self-service and failed. Monitoring AI performance will become an operational KPI itself (e.g., containment rate, AI success vs. failure cases).
Alignment with Enterprise Needs: On the whole, Dialpad’s feature set and vision align with many trends and needs in enterprise contact centers:
Improving Customer Experience: Enterprises aim to improve CSAT, reduce customer effort, and resolve issues faster. Dialpad’s AI coaching, aiCSAT, and eventually agentic AI all target better experiences – either through faster answers (AI assist) or proactive service (agentic AI). The pre-emptive service concept is essentially about low-effort customer experience (solving issues before the customer even has to ask, as Gartner noted agentic AI enabling “low-effort experiences”). That’s aligned with the strategic goal of many CX leaders: to increase customer loyalty by making service seamless and easy.
Operational Efficiency and Cost Management: Contact center leaders are pressured to handle growing interaction volumes without commensurate budget increases. AI promises efficiency gains, and Dialpad’s current AI has delivered some (AHT reduction, etc. ). The autonomous future promises even more (automating whole tasks). Features like auto call logging to CRM and WFM adherence tools also streamline operations. Enterprises want to reduce agent burnout and attrition – Dialpad cites a 10% drop in agent turnover due to reduced workload, which if true is a big win since turnover is costly. So these tools aligning with the goal of doing more with less, and making agents’ jobs less tedious, are likely to be well received by ops managers and CFOs alike, provided they deliver as advertised.
Enterprise Integration & Compliance: Enterprises need new tech to integrate with what they have and meet compliance. Dialpad’s attention to integrations (CRM, Teams) and security (Intune, RBAC, data governance) is directly aligning with those needs. For example, many large companies have strict device management – Intune support addresses that. Data sovereignty and multilingual support are key for global companies – Dialpad adding languages and compliance tools speaks to those concerns. By working toward Microsoft Teams certification, Dialpad aligns with enterprises that standardize on Microsoft ecosystems.
Analytics and Insights: Enterprises are hungry for better insights from the contact center (to drive improvements or business decisions). Dialpad’s enhancements in analytics (aiCSAT, digital scorecards, semantic insights) align with this need, though as noted, others like EndeavorCX might still have an edge. At least Dialpad is beefing up its analytics offering so enterprise clients don’t feel they need a separate speech analytics tool – they can potentially get a lot from Dialpad’s built-in capabilities. If that proves true, it’s a cost saving (one less vendor/tool to manage).
Scalability and Reliability: Enterprise alignment also means being able to handle scale. The mention of 1,500 participant meetings and large-scale features implies Dialpad is ensuring its infrastructure can handle big loads. Enterprises will test this – e.g., can Dialpad reliably handle thousands of concurrent calls, with AI processing on each? Early indications (Dialpad supporting large customers like T-Mobile, Netflix per their customer list) suggest yes, but each new AI feature could introduce performance considerations.
A potential misalignment could be if an enterprise is not ready culturally or strategically for certain AI elements. Some very conservative organizations may not want AI making customer-facing decisions yet. Dialpad’s vision might outpace what such companies are comfortable with in the near term. Conversely, very cutting-edge clients might find Dialpad’s timeline slow – if they want to implement advanced AI now, they might lean to assembling best-of-breed solutions rather than waiting for Dialpad’s fall 2025 release. It’s a balancing act.
Gaps, Opportunities, and Potential Market Reaction
No announcement is perfect; it’s important to identify gaps in Dialpad’s strategy and offerings, as well as opportunities these present – either for Dialpad to improve or for customers/competitors to respond. Additionally, we’ll gauge the market reaction and sentiment likely to follow these announcements.
Gaps in Dialpad’s Announcements:
Vision-Product Gap: The most evident gap is between the Agentic AI vision and currently available capabilities. There’s a timing and credibility gap here – Dialpad is effectively asking the market to trust that it will deliver a revolutionary platform in about a year’s time. In the interim, competitors might argue Dialpad is selling hype. Customers might also pause: should they wait for Dialpad’s Agentic AI before making a move, or choose a competitor that has more AI functionality today? This gap opens an opportunity for competitors to swoop in with “available now” solutions. For instance, a rival could say, “Why wait for Dialpad’s fall 2025 autonomous AI, when you can deploy our AI bots or analytics in summer 2025 and start saving money now?”
Depth of Analytics: While Dialpad is improving its analytics (aiCSAT, etc.), there might be a gap compared to specialized analytics providers (like EndeavorCX’s Vitalogy). Dialpad’s press materials focus on certain metrics and use cases, but they don’t mention things like sophisticated journey analytics, customer effort scoring, or cross-channel linkage at the level Vitalogy does. If an enterprise’s priority is deep insight rather than operational tools, Dialpad’s built-in capabilities might still fall short. This is an opportunity for Dialpad to either partner (though their messaging is all about native AI) or to further develop their analytics layer to truly rival the likes of Vitalogy’s semantic engine. It’s also a gap where a customer might decide to augment Dialpad with a dedicated analytics solution (which somewhat dilutes Dialpad’s all-in-one value prop).
Omnichannel Self-Service: Dialpad’s Agentic AI examples were mostly voice or traditional interaction oriented (calls for order tracking, voice for appointment scheduling). There wasn’t explicit mention of omnichannel bot strategy – e.g., will these AI agents also operate on chat/web, or only phone calls? Likely they will do all, but clarity is lacking. Also, “pre-emptive service” could involve proactively reaching out to customers (outbound notifications of issues solved). Dialpad didn’t detail any proactive outbound capabilities (e.g., auto-emailing a customer when a known issue is resolved). This might be a gap in the vision – focusing on inbound handling rather than true outbound pre-emption. Competitors like [hypothetical example] could say they have proactive journey orchestration already. So Dialpad might need to expand the narrative to cover outbound use of AI for it to be fully “pre-emptive”.
Customizability and Openness: Enterprises often want to fine-tune AI to their business. It’s not clear how much Dialpad will allow customization of the AI models or access to the raw data. EndeavorCX’s approach is very open (APIs, etc.), whereas Dialpad, as a closed platform, might not easily let you export all interaction data or embed its AI elsewhere. If an enterprise has a data lake and wants to run their own AI on call data, can they get data out of Dialpad easily? They did mention APIs and integrations, but it’s a potential gap if Dialpad’s AI is mostly a black box that you can’t tweak. This might affect highly regulated or specialized industries that need visibility into how AI decisions are made (though Dialpad presumably provides some explanation for aiCSAT factors, aligning with the interpretability trend).
Workforce Impact Acknowledgment: Another gap is an explicit discussion of how agent roles evolve. Dialpad (like many vendors) glosses over the fact that if AI handles more tasks, the role of human agents and supervisors will change significantly. This is more a narrative gap – an analyst might want to hear how Dialpad envisions the human-AI collaboration model, not just in technology but in org structure.
Opportunities:
First-mover Advantage (if executed): If Dialpad can deliver functional autonomous AI capabilities by 2025, it can claim a first-mover advantage among CCaaS peers. Many contact center providers are still in the phase of augmenting agents rather than replacing tasks. Dialpad has openly set a marker. Should they succeed, they can capture mindshare and some market share from companies eager to leverage that tech. There’s an opportunity to gather compelling case studies (e.g., a retail client whose AI agent handles 30% of calls with high CSAT – that would be headline-worthy). So the window from now to late 2025 is Dialpad’s chance to prove their vision, and if they do, they could leap ahead of slower-moving competitors.
Upselling and Customer Retention: The new features (especially aiCSAT, WFM, etc.) give Dialpad upsell opportunities within their base. For existing customers, Dialpad can now sell additional modules or higher tiers that include these advanced AI analytics and WFM tools. This not only drives revenue but also increases stickiness – the more functions a customer relies on Dialpad for, the less likely they switch. Also, the vision can be used by account managers to retain customers: “Stay with us, we have exciting stuff coming that you’ll get as part of our roadmap.” The opportunity is to convince customers that Dialpad is the platform to grow with, not one to leave for a more advanced competitor.
Partnerships to Fill Gaps: Dialpad might not publicly emphasize this, but it has an opportunity to partner where it lacks expertise. For example, if building out all those autonomous workflows proves challenging, they might integrate a third-party AI orchestration or RPA solution under the hood, or partner with system integrators to deliver custom AI agents for clients. Similarly, partnerships with consultants could help customers adopt the changes (change management). While the marketing is about native AI, pragmatically, Dialpad could accelerate time-to-value through ecosystem collaboration. This would help ensure the vision doesn’t falter due to trying to do everything alone.
Marketing and Thought Leadership: Dialpad stepping forward with the “Agentic AI” concept (even the terminology) is an opportunity to be seen as a thought leader. If they contribute to industry discussions (webinars, whitepapers) on pre-emptive service and agentic AI, they can shape the narrative. Opportunity also lies in aligning with Gartner’s concept publicly (they already cite Gartner’s term in the PR). If they can showcase a demo at, say, a Gartner conference later in the year, it would reinforce their leadership stance. Essentially, the gap between vision and reality can be narrowed perceptually by actively demonstrating progress.
Potential Market Reaction:
Customers (Enterprises): Enterprise reaction will likely be cautious curiosity. Many will be intrigued by the idea of pre-emptive AI service (some may forward the press release internally with “FYI – interesting direction”). Existing Dialpad customers might be pleased that their vendor is innovating (reducing fear of missing out on AI) and will look forward to trying the new features like aiCSAT. However, they’ll likely want to pilot and validate before rolling out widely. For prospective customers evaluating solutions, the announcements could put Dialpad on their radar or bump it up in consideration, but most will still insist on seeing proof. The slightly cynical ones might say “Sounds great, but let’s see if they can actually do it; we’ll re-evaluate next year once it’s real.” A few cutting-edge clients might volunteer for early access (the press release invites that), which is positive as long as those go well.
Industry Analysts and Commentators: Analysts may give Dialpad credit for an ambitious vision and notable improvements, but with the caveat of “execution will be key.” Some might recall previous hype cycles and advise end-users to temper expectations. If we consider EndeavorCX’s briefing as an indicator, analysts value depth and actual innovation. Vitalogy was praised for substance over marketing fluff. Dialpad’s news might get a bit of skepticism in comparison (“Dialpad announces big AI plans, but others like EndeavorCX are already delivering rich AI insights today” could be a sentiment). However, analysts who cover CCaaS will likely note that Dialpad is evolving into a more serious enterprise contender. The presence of concrete feature upgrades helps – it’s not only a pie-in-sky announcement.
Competitors: Competing vendors will respond in a few ways. Established CCaaS players (e.g., Genesys, Five9, NICE/InContact) might publicly congratulate the focus on AI (as it validates the overall direction) but privately they’ll arm their sales teams with counterpoints. They might emphasize Dialpad’s inexperience in large complex deployments or question the maturity of its AI. Competitors with existing AI solutions will highlight those: for instance, “We already have AI XYZ that can do similar things today.” EndeavorCX itself, being singled out as a gold standard in our analysis, would likely highlight that Dialpad’s vision reinforces EndeavorCX’s approach – essentially saying “We’re glad others see the need for semantic, proactive AI. By the way, Vitalogy already offers the core of what Dialpad is promising, minus the CCaaS, and you can use it right now.” They’ll particularly point out that Dialpad’s platform-centric approach forces you into their ecosystem, whereas EndeavorCX’s is open (a selling point for enterprises hesitant to change core call platforms). In competitive bake-offs, we might see pitches like “Dialpad talks about agentic AI; here’s a demo of our bot handling a task right now,” if those competitors can muster such a demo.
Market Trend Influence: If nothing else, Dialpad’s aggressive marketing of “Agentic AI” could spur a broader conversation and possibly pressure others to articulate their own visions. It might push the industry faster towards discussing autonomous agents as a near-future reality rather than a distant one. This could lead to a bit of an “AI vision race” where each vendor showcases their roadmap (which, cynically, can sometimes lead to over-promising across the board). Market reaction might include some skepticism from buyer organizations that fear hype – the more every vendor claims AI magic, the more some customers tune out until they see proof. Dialpad will want to avoid being lumped into “AI hype noise” and ensure it stands out with credible advancement.
In summary, the market reaction is expected to be a mix: Interest and optimism tempered by skepticism. Dialpad’s announcements will be seen as a positive sign that the platform is growing up and innovating, but the separation of vision vs. current capability won’t be lost on the audience. Savvy customers and competitors will probe that gap. Dialpad has an opportunity to capitalize on the buzz by quickly following up with real demos, customer success stories, or technical deep-dives to show there’s substance behind the slides. If they handle the follow-through well, they can turn initial cynicism into genuine enthusiasm. If not, the risk is being seen as more talk than walk.
Conclusion and Recommendations for Decision Makers
Dialpad’s recent announcements mark a significant moment in the contact center technology landscape – one that blends immediate practical enhancements with a bold promise for the future. For contact center decision-makers, the takeaway is that Dialpad is a vendor striving to innovate and close gaps, but one must carefully separate the ready vs. the not-yet-real when considering it as a solution.
In conclusion, Dialpad is emerging as a serious contender for enterprises, thanks to its infusion of AI throughout the platform and attention to enterprise integrations and controls. The “Agentic AI” vision demonstrates thought leadership by aiming at what many believe is the next frontier of CX (autonomous, proactive service). Yet, the difference between launching a vision and delivering outcomes cannot be overstated – Dialpad will need to execute methodically to prove that its AI can truly take customer service to the next level. Until then, its new features like Ai Live Coach and aiCSAT provide value that is more incremental in nature, helping improve today’s operations and agent performance.
For decision-makers evaluating Dialpad in light of these announcements, here are a few recommendations:
Leverage Today’s Features, Plan for Tomorrow’s: If you are a current Dialpad customer, take advantage of the new capabilities that are available now. Implement the aiCSAT scoring in your QA process to get a broader read on customer sentiment. Use the improved coaching and CRM integration to streamline agent workflows. These can likely drive measurable improvements (as evidenced by Dialpad’s other customers and the TEI study) while you keep an eye on the development of Agentic AI. If you are considering Dialpad, factor these features into your ROI analysis – they add to the platform’s utility even without the future vision. At the same time, engage with Dialpad’s roadmap: inquire about pilot opportunities for the Agentic AI platform, and assess how those future capabilities might fit your long-term strategy. Essentially, adopt a “win now, win later” approach – get benefits in the near term, and position your organization to capitalize on the autonomous features when they mature.
Maintain Healthy Skepticism (Ask for Evidence): Embrace the possibilities Dialpad is offering, but require proof points. Before betting critical customer interactions on AI, ask Dialpad for demonstrations or case studies of their AI in action. Since the fully autonomous pieces are not out yet, focus on what’s measurable now: e.g., how accurate is the aiCSAT score vs. our existing survey results? Can we run a trial to compare? How much does AI Live Coach actually reduce errors or improve handle times in a similar deployment? Use those metrics to gauge Dialpad’s AI effectiveness. This not only validates the product for your peace of mind, but it also signals to Dialpad that you expect rigor, which can encourage them to prioritize transparency and results over hype.
Consider the Competitive Context: When making purchase or upgrade decisions, compare Dialpad’s offerings with those of competitors (like EndeavorCX’s Vitalogy or other AI-enabled platforms). If high-level semantic analytics and open integration are top priorities, see how Dialpad’s conversation intelligence stacks up against Vitalogy’s semantic engine approach. If having an independent AI layer appeals (to avoid lock-in), weigh the pros and cons of Dialpad’s all-in-one solution vs. a combination of a CCaaS plus a separate AI platform. EndeavorCX’s gold-standard status in AI suggests that one could achieve a very advanced setup by layering something like Vitalogy onto an existing contact center. On the flip side, Dialpad’s integrated approach might mean less complexity and potentially lower total cost if it meets your needs. Benchmark features and ask vendors to clarify not just what they have now, but what is truly productized vs. experimental. EndeavorCX’s strengths in real-time KPIs and multi-channel analysis set a bar; use that bar in discussions with Dialpad (and others) to ensure you’re getting the best of breed for whichever path you choose.
Assess Organizational Readiness: If you intend to ride the wave of these AI advancements, prepare your organization. Start training your teams on how to interpret AI-driven insights (for instance, ensure QA analysts understand how aiCSAT works and its limitations). Begin updating agent training to include responding to AI prompts. If autonomous agents are on the horizon, involve your operations and IT teams in laying the groundwork: identify which processes could be handed to an AI agent first (e.g., password resets, order status queries) and ensure those back-end systems have APIs ready for Dialpad’s AI to use. Essentially, align your people, processes, and data for AI integration. This way, when Dialpad (or any vendor) brings new AI capabilities, you can pilot them faster and more successfully.
Watch for Gaps and Mitigate: Keep an eye on any gaps that might affect you. If you require something Dialpad doesn’t yet offer (e.g., advanced journey analytics or an on-premise option for certain components), plan around it. Maybe that means using Dialpad for core interactions but supplementing with another tool for that need in the short term. Or pushing Dialpad on their roadmap for that feature. Recognize that no single platform does absolutely everything perfectly – the goal is to see if Dialpad’s direction aligns with your priorities and if any interim gaps are manageable. The good news is, Dialpad’s trajectory suggests many gaps are closing.
Stay Agile in Strategy: The contact center technology space is moving quickly. Today’s vision announcements might become tomorrow’s standard features – or they might prove more challenging than expected. Maintain an agile strategy: be ready to pivot if, say, another vendor suddenly offers a proven autonomous service that outperforms, or if Dialpad’s deliveries slip. Avoid locking into long contracts purely on promises; ensure you have checkpoints where you can evaluate if reality is meeting expectations. In other words, embrace innovation, but protect your flexibility.
In the end, Dialpad’s push with Agentic AI and enterprise features is a positive sign of an industry innovating to solve age-old customer service challenges with new tools. It reflects a broader evolution: contact centers are becoming experience hubs powered by AI, data, and automation rather than just call-taking silos. Dialpad’s vision contributes to that evolution. For contact center leaders, the task is to harness these innovations pragmatically – adopt what yields better customer and business outcomes, remain critical of what is not yet proven, and foster a partnership with vendors like Dialpad that holds them accountable to delivering on their ambitious claims. By doing so, you can turn a vendor’s vision into your organization’s competitive advantage, all while steering clear of the pitfalls that sometimes accompany bleeding-edge technology.
Ultimately, the slight critical analysis we’ve maintained in this analysis serves as a reminder: in customer experience, as in all things tech, it’s wise to hope for transformation but plan for iteration. Dialpad has signaled where it’s heading; now the ball is in their court to follow through, and in yours to leverage these developments to the benefit of your customers and your contact center’s performance.
Sources:
Dialpad Press Release – “Dialpad announces a vision of Pre-Emptive Customer Service with Agentic AI and enterprise platform enhancements,” May 13, 2025.
Dialpad Blog – “Elevate Your Enterprise Contact Center: New Dialpad Features & Upgrades,” May 2025.
ActivateCX Briefing – “Vitalogy Unleashed: The AI Core Rewiring CX Intelligence,” Apr 24, 2025.
Gartner Research via TechMonitor – “Agentic AI to automate 80% of customer service queries by 2029,” Mar 6, 2025.
Dialpad Customer Success Example – Foley (via Dialpad press release).
Dialpad Platform Data – Forrester TEI Report stats (via press release).
EndeavorCX Vitalogy Principles – VitalogyCX site.