We have been lying to ourselves since, well, basically since forever. We placed customer support agents into a padded room called the "contact center," handed them a ticketing system, and told them to keep the angry people away from the rest of the business. We tracked average handle times; we cheered when a routing algorithm saved a fraction of a second; and we pretended that managing an interaction was the same thing as solving a problem. Deflecting an issue was the holy grail.

That era is over. The walls of the contact center have been blown wide open, and the debris is currently raining down on the CRM and operations landscapes. The market is shifting from asking the question "who can capture the ticket best?" to "who can actually resolve the problem fastest?” Which is an entirely different category of question. And far more meaningful.

And as Cameron Marsh from Nucleus Research so accurately pointed out in our recent CRMKonvo, that is a much nastier, much more complex place to compete.

TL;DR

If you want to watch the full CRMKonvo, please go ahead here (optimized for smartphones) or here (optimized for tablets/computers).

Else, be my guest and continue to read.

Or feel free to do both …

The Illusion of the "Smart Ticket"

Let’s just be absolutely clear from the start: nobody wants a ticket. A ticket is simply a formalized receipt of failure. It is documented proof that a product broke, a service failed, or a user interface was too clunky to navigate.

For years, many vendors, including specialists like Zendesk, Freshworks, and others have built success around making those tickets prettier, easier to handle and pass around. And companies like Five9, Genesys, Verint and too many more to count happily managed the interaction center. But when Salesforce forcefully entered the CCaaS conversation with new voice and AI capabilities, they fired a warning shot across the bow of every standalone service vendor. Salesforce is betting that because they own the underlying customer data and the core business workflows, they should own the resolution. They are not selling a better queue; they are selling an operations layer.

The response from the service-first vendors is equally bold. They argue that because they capture the initial intent and handle the front-line friction, they are ideally positioned to resolve the issue before it ever touches a core system.

But the time-honored truth is that buyers do not really care about these architectural turf wars. Customers do not care if your platform uses a sophisticated LLM or a massive RAG implementation. They care about one thing: when something breaks, who fixes it? If your AI simply routes a ticket more efficiently to a human who still has to manually process a refund across three legacy systems, your AI is nothing more than expensive window dressing, or as Cameron aptly put it, “automation with a better branding”.

Smelly Data and the LLM Mirage

Which brings us to the most uncomfortable reality of the current enterprise software hype cycle: the data problem. Every vendor is currently parading their AI Agents and "AI Studios" around like magic wands that will instantly get things done while vaporizing operational costs.

But as we discussed on the show, almost every organization suffers from what we fondly call smelly data. They have decades of poorly categorized customer records, duplicate entries, and contradictory knowledge base articles. Pointing a state-of-the-art LLM at a mountain of unwashed data does not give you artificial intelligence; it gives you a very fast, very confident artificial idiot.

Garbage in equals garbage out. It is a cliché because it is true. The organizations that are actually seeing a return on their AI investments are not the ones buying the flashiest tools. They are the ones putting in the hard and unglamorous work of normalizing their data models, cleaning up the data and integrating their core systems. If you do not have a pristine data foundation, your generative AI will simply generate more work for your human employees to clean up while chasing your customers down rabbit holes.

The "Suite vs. Best-of-Breed" Debate Reignited

For the last decade or so, the enterprise software pendulum swung heavily toward "best-of-breed." We bought point solutions for every micro-problem and relied on brittle APIs to hold the Frankenstein monster together.

The trend slowed a few years and nowadays AI is starting to violently push the pendulum back toward the suite, or at least a platform. When you deploy an AI agent to resolve a customer issue, that agent needs instantaneous, read-and-write access to lots of data, often including billing, shipping, inventory, and customer history. Every single integration point is a potential point of failure. Every seam between different software vendors is a place where context gets lost and the AI starts to hallucinate.

As Cameron noted, the burden of proof has shifted. It is no longer up to the suite vendors to prove they are better. It is up to the best-of-breed vendors to prove that their necessary integrations will not slow down the AI or destroy the seamless execution of a workflow. If an integration creates lag or drops context, the ROI of the entire project collapses. The suite wins not because it has the best individual features, but because it has the fewest broken bridges while being good enough to do the job.

The True Predictor of Success: It Is Not the Tech

Here is the most interesting takeaway from Cameron and Nucleus Research evaluating dozens of successful AI implementations: the specific technology stack rarely predicts the success of the project. Whether a company chose Salesforce, Zendesk, or a bespoke solution, the common denominator of success was the human element.

The companies that succeed have a stellar relationship with their vendor's Customer Success Management team. They admit what they do not know, they ask for help with workflow design, and they partner with their vendors rather than treating them like mere order-takers. Conversely, the CSM teams admit where their software might not be the one to go for. It’s a two-way street. The technology is just the engine; the vendor relationship is the steering wheel. If you buy a Ferrari but refuse to talk to the mechanic, you are going to crash.

Reality Check: Three Imperatives for Enterprise CX Buyers

If you are a CIO, CXO, or IT leader currently evaluating AI for your service operations, you are swimming in an ocean of marketing fluff. Vendors are promising to cut your headcount in half while doubling your customer satisfaction. To avoid making a catastrophic and expensive mistake, here are three critical learnings you must apply to your buying cycle today.

Stop Buying "Deflection" and Start Buying "Resolution"

Deflection is a vanity metric. Often, a high deflection rate simply means you have made your IVR or chatbot so incredibly frustrating to use that the customer gave up and went to a competitor. Do not reward vendors for preventing customers from reaching you.

Instead, force vendors to prove their "fully resolved" rate. Demand to see how their AI handles a complex workflow end-to-end without a human ever touching it. If the AI can only handle password resets and order status checks, it is just a basic automation script wearing a tux. You are paying an "ego tax" for a label. Demand actual resolution.

Clean Your Pipes Before You Buy the Pump

Do not spend a single dollar on an AI agent if you have not invested time and resources to clean your data. The most sophisticated LLM in the world cannot resolve a billing dispute if your billing data is housed in an on-premise server from 2012 that only updates in batches every 24 hours and doesn’t even offer an API.

You need to establish a rigorous knowledge management practice. You need clean, structured data and clear workflow documentation. If you skip this step, your AI implementation will fail, your ROI will evaporate, and you will spend the next two years blaming the software for a problem that you created on your own.

Calculate the True "Human-in-the-Loop" Maintenance Cost

Vendors love to show ROI models based on how many tier 1 support agents you can eliminate. What they conveniently leave out of the spreadsheet is the cost of the highly skilled engineers, data scientists, and workflow managers you will have to hire to babysit the AI.

An AI system requires constant tuning, monitoring for hallucinations, management of drift, and edge-case management. You might eliminate fifty low-cost roles, but you will need to hire five very expensive experts to maintain the system. The need for humans in the loop further reduces the systems autonomy and hence “efficiency”. If your ROI calculation does not account for this shift in personnel costs, you are presenting a work of fiction to your board. Focus on the payback period, don’t forget about ongoing maintenance costs, and never buy a black box that your own team cannot audit.

The past weeks showed quite some interesting activity on the mergers and acquisitions and the partnership frontiers. NiCE acquired the German conversational AI rock star Cognigy for $955M and a short time later announced that the company enhanced its partnership with Salesforce. At nearly the same time, Genesys received an additional funding of $1.5 bn from Salesforce and ServiceNow. Salesforce acquired Waii and Bluebird. VC company Thoma Bravo acquired the still leading CCaaS vendor Verint, to name but a few of the more interesting, and perhaps consequential ones.

On top of all this, Avaya seems to have offered all employees a voluntary exit package.

What all this shows is that there is significant consolidation going on in the AI-assisted (or should I say, driven?) CCaaS market and that various players are battling to provide – or at least be perceived to provide – the most comprehensive and valuable platform while others fight for survival.

Yes, it’s nothing new, but can’t be repeated often enough. The CX market is and always was a high stakes platform game. The stakes got even higher with the advent, the promise and the necessary investments that generative AI and agentic AI require. While one can consider Salesforce’s acquisitions as tuck-ins that help rounding off its Agentforce platform, the other ones are a sign of something bigger going on in the CCaaS and customer service market segments. It is also notable that exactly these sectors get more and more referred to as CX market, whether this is a correct, or only good, attribution, or not. Hint: It isn’t.

Not unexpectedly, Salesforce is in the thick of all this, having a massive stake in Genesys and a strategic – at least for NiCE – partnership with NiCE. And regardless, of whether NiCE or Genesys turn out to be stronger, Salesforce wins.

For customers of the Salesforce ecosystem this, first of all, gives choice. For Salesforce, it gives access to a wide array of different customers and therefore the ability to fuel the data pipeline that Agentforce needs. With the different profiles of NiCE/Cognigy, customers need to establish for themselves whether they need the strengths on the customer service center side (NiCE/Cognigy) or the analytics and orchestration side (Genesys).

On the other hand, we have Verint getting into the fold of Thoma Bravo and being merged with WEM vendor Calabrio. This instantly creates a strong player that includes WEM and analytics capabilities. But looking into the Thoma Bravo portfolio, there is more, in particular Medallia. Adding Medallia’s capabilities adds improved journey management and especially a strong voice of the customer element that helps understanding and therefore improving customer sentiments at every single touch point. This would challenge CCaaS leaders like Genesys and NiCE by creating a comprehensive analytics story and a journey orchestration capability. With the help of UserTesting this gets even more pronounced as UserTesting’s technology allows the finding of a root cause of a problem identified using the Verint/Calabrio/Medallia stack. This combination can create something that one could call a total engagement and analytics platform that covers the capabilities of traditional customer service vendors, CCaaS vendors, and journey orchestration vendors. This has the potential to create a tectonic shift in these software categories, as they converge to form a kind of Gondwana of service solutions.

While this doesn’t necessarily create an immediate threat to the Zendesks and Freshworks of this world, it may severely limit their ability to enter into more complicated, multi-step service scenarios. On the other hand, this combination of Thoma Bravo capabilities needs to prove its ability to scale down to avoid being disrupted from below by vendors that have their strength in high volume ticketing scenarios.

I do not know whether this is what Thoma Bravo has in mind, but the scenario is quite appealing to me.

My analysis and point of view

But in any case, one thing is clear: The markets for conversational/agentic AI, CCaaS, UCaaS and customer service are converging while the markets are consolidating. And all of this seems to accelerate around two themes that NiCE and Genesys exemplify.

NiCE's is integrating vertically. The Cognigy acquisition is an integration move that aims at owning the full technology stack, from core CCaaS to best-in-class conversational AI. The goal is a seamless, single-vendor platform. The risks for customers are potential integration debt from the acquired asset, a less open and smaller ecosystem, and probably a premium licensing for these new capabilities after being locked in. The deepened Salesforce partnership is a pragmatic necessity to ensure relevance and access to the bigger ecosystem, not a fundamental strategy shift.

Genesys plays the ecosystem card. The capital injection from Salesforce and ServiceNow is probably a direct counter. It funds a horizontal integration strategy, betting that enterprises prefer a tightly integrated alliance of market leaders over a single-vendor suite, which is in line with both Salesforce’s and ServiceNow’s strategies. The risk is that these integrations remain shallow, and the "ecosystem" is more of a marketing concept than a technical reality. This largely depends on how the three parties build and execute their roadmaps.

Thoma Bravo’s portfolio around Verint can become a wildcard theme here. The merger of Verint and Calabrio would create a third force. This entity would not necessarily compete directly on the CCaaS infrastructure layer but would focus on the higher-margin levels, starting with WEM and interaction intelligence. Combined with the other portfolio companies, its power would come from either being a platform-agnostic integration hub—the "Switzerland of data" or becoming another vertically integrated solution.

With this convergence going on, customers will be able to create data informed and more seamless processes for their customers, simply because there will be deeper integration on a data platform level, not necessarily a software platform one.

What should customer executives look at now?

• NiCE/Cognigy customers face significant integration risks due to two leading technologies being combined. Customers should demand a detailed, time-bound integration plan and roadmap with technical milestones. They need to have a deep and hard look at how their current licensing models are changed by new ones and model their TCO inclusive of probable premium "Cognigy-powered" features.
• Genesys customers face a different execution risk. They require technical proof-of-concepts that demonstrate the depth and real-time nature of the Salesforce and ServiceNow integrations, respectively, along with a detailed integration roadmap. They should mandate that business value metrics be tied to the pricing and success of this "ecosystem."
• Verint and Calabrio customers face a similar integration risk plus an uncertainty about the detailed positioning and future of Verint. Customers need to demand a detailed integration roadmap with milestones and clarity about the final strategy – platform neutrality or vertical integration.
• Avaya customers are worst off – and have been for a while. Avaya is in survival mode. This situation requires immediate risk mitigation. Customers should work with a two-prongued strategy: Firstly, they need to secure existing SLAs and support commitments in writing. Secondly, they need to engage in a RFI/RFP process for at least two cloud-native CCaaS platforms. The objective is to have a fully vetted exit strategy that can be executed fast.

Some general recommendations

There is so much going on at a fast pace, that it pays off to reevaluate vendor roadmaps. An outdated understanding of your vendor's strategic position is a serious liability. The market of 18 months ago does no longer exist and the market of in 18 months will be very different from today’s.

As platforms consolidate, the risk of vendor lock-in increases. Customers should favor providers with a demonstrated commitment to an open, API-first architecture. There is no one-size-fits-it-all software platform for all businesses, nor will there be.

The current market will expose providers with weak financial fundamentals. Customers should review their vendor’s financial health and R&D investment as a default part of their due diligence.

Last, but not least, customers need to avoid AI-washing and require that any proposed AI solution be tied to a business case with measurable outcomes, such as reduced operational costs or improved containment rates. Additionally, contracts need to be tied to achieving these outcomes.