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The headlines from InfoComm 2026 said the industry moved “from rooms to experiences.” We’ve been observing this transition for a while. But what’s more relevant to anyone who buys, runs, or just sits in meeting rooms is that the room has become another device on the corporate network, and that changes who is in charge of it. 

For years, the meeting room was the thing on the wall you hoped would just work. InfoComm 2026 in Las Vegas, the pro AV industry’s big annual show, made the case that those days are over. The room is no longer a fixed installation. Yes, it is becoming an experience, but it also bears a striking resemblance to something IT knows all too well, a textbook case of AV/IT convergence: a managed device, bought like an endpoint, run like part of a fleet, and increasingly able to collect data about the people inside it. 

The industry has agreed on the theme: outcomes, not spec sheets, now drive what companies spend on collaboration technology. Buyers want rooms that simply work and that prove their value. But what’s worth exploring is how they get there. What is different in how a meeting room is bought, run, and governed? And who ends up operating it? 

Let’s look at some numbers. Attendance at InfoComm 2026 fell about 9% year on year. What rose was the share of buyers in the room. AVIXA (the Audiovisual and Integrated Experience Association, which owns and produces InfoComm) reported that end users made up 37% of attendees, a record, up from 35% last year and 29% in 2024. So fewer people came, but more of them were the ones who sign the purchase order. What they found was a transitioning market: value is continuously moving away from hardware and installation labor toward software, cloud, and AI. 

Three groups of announcements at the show summarize this: one each for how a room is bought, how it is run, and how it is governed. 

Your next room upgrade starts with the chip that runs on-device AI 

For years, a room upgrade meant better cameras, microphones, and displays. InfoComm 2026 reframed it as a decision about processing power. HP introduced its Poly Studio Room Compute, and Cisco showed new endpoints, built on an operating system called RoomOS 26 that it developed with NVIDIA, that run AI agents directly on the device rather than in the cloud, an approach some now call edge AI. 

Cisco leaned hardest on this point, and the argument threaded through the entire show: the features that do real work in a meeting, not just record it, need on-device AI processing, so a room built on incompatible or aging hardware simply cannot run them. In other words, AI in the meeting room is no longer only a software question. It’s about hardware. Perhaps the more uncomfortable part for most buyers is that a lot of the equipment bought in the last few years may not run the features now being sold, which turns a routine refresh into a spending decision that requires a business case. 

Enter the agentic AI 

Think about what happens today when a meeting room misbehaves. Someone files a ticket and waits for a technician. Well, according to InfoComm 2026, you will soon be asking an AI assistant to sort it out. 

Several vendors connected their room systems to AI assistants using the Model Context Protocol, the open standard that companies are adopting to let AI act on their other software. Neat’s version runs on your own network and works with assistants like Claude or Cursor, so the assistant can see what is wrong in a room, change the settings, and resolve common problems without specialist knowledge or a site visit. Others are taking their own routes to the same idea: Shure, the show’s headline partner, is moving beyond hardware with ShureCloud, which manages devices centrally and adds an AI assistant for troubleshooting and support, while Cisco has connected Microsoft’s Copilot to Webex. Related tools now watch over rooms from many brands, and across Teams, Zoom, Google Meet, and Webex, from one place. 

Why should anyone outside AV care? Because this is the same move toward AI agents that is happening across the workplace, only now reaching the meeting room, and the payoff is both money and time saved: fewer call-outs, fewer help-desk tickets. It also pushes the firms that install AV toward ongoing service instead of one-off projects. However, it is still early. Most of this was shown as a capability, not a full rollout, and whether “agentic” lives up to the label is still unproven. 

So the room is now collecting data. But who governs it? 

The moment a room becomes “intelligent”, it starts producing data: who was in it, who spoke, and how the space was used. That makes it interesting to a lot more people. HR, legal, and security now have a stake in it, alongside IT, and each comes at it from a different angle. 

HR sees a room that can log who attended, who spoke, and how much, and wants to reassure employees that this isn’t being used against them and retain their trust. Legal sees the recordings and transcripts as personal data: information that carries consent, retention, and residency obligations, and that can be pulled into discovery if a dispute arises. Security sees a networked device sitting in on confidential conversations and asks the obvious questions, namely who can access that data, where it is stored, and how much bigger a target the room has become. IT, which used to own the room outright, now runs it on behalf of all three. And there is still no security standard written specifically for AI in these systems, and general ones like NIST cover only part of it. 

The industry’s early answer is to keep the processing and the data inside the room rather than sending it to the cloud, which helps with privacy and with rules about where data is allowed to live. Those questions are climbing the data governance priority list for IT and security teams this year, and writing the policy before you roll rooms out widely saves you the harder job of untangling it later. 

The room reads you now. Time to read the room. 

The meeting room is now bought like any other endpoint, run as part of your device fleet, and governed as a data source. That is a long way from the box on the conference-room wall. 

What to do before your next upgrade:  

  1. Ask which AI features run on the hardware you already own, and what you would need to buy for the rest.  
  1. Before you believe any “agentic” pitch, run a small pilot and hold it to a measurable result, such as fewer support tickets.  
  1. And before you scale, decide who owns the data the rooms collect.  

Do that, and the answer to who operates your meeting rooms, AV, IT, or an AI agent, becomes all three, working alongside. The companies that treat the room that way will get the most out of what vendors are now building. 

Navigate your next workplace technology decision with the evidence to back it. Explore IDC’s Intelligent Workplace research, forecasts, and analyst guidance, or speak with our analysts. 

Gala Spasova

Gala Spasova - Senior Research Manager, Europe Smart Office and EMEA Content & Knowledge Management Strategies

Analyst Profile
Gala Spasova is a senior research manager in IDC's Future of Workplace & Imaging team. Her research focus is on Hybrid working, Smart Office technology and Content & Knowledge Management Strategies in EMEA.  Spasova is also part of the European…

IDC recently brought together 20 senior technology executives for an invitation-only dinner with analysts Carla Arend, Andrew Buss, Duncan Brown, and Rahiel Nasir to discuss digital sovereignty in Europe. Here’s what came out of the room.

Sovereignty is real. The conversation around it isn’t.

IDC opened with a provocation: the word “sovereignty” is doing more harm than good. It’s politically loaded, definitionally contested, and vendors have been guilty of “sovereign washing”. Meanwhile, IT departments struggle to translate the concept into something their internal stakeholders actually care about.

What European organisations do care about is entirely concrete: protection against extra-territorial data requests, regulatory compliance, and supply chain resilience. According to IDC research, these are operational risk priorities, not political statements. The vendors making progress in this space have figured out how to speak to that gap. Those still foisting their own definitions of sovereignty on to the market and/or offering nothing more than so-called solutions for data localisation/residency largely haven’t.

The cloud strategy picture is more nuanced than the headlines suggest

Europe is re-assessing its options for cloud and technology providers. Global hyperscalers remain part of the picture, but how they are used is increasingly open to question. IDC’s data points to a clear shift toward layered architectures that combine global scale with local control. A specific model is emerging as the dominant pattern, and the vendors positioned within it are seeing very different conversations than those sitting outside it.

The regulatory picture adds another layer of complexity. NIS2, DORA, the AI Act: each creates compliance obligations that directly shape how organisations think about their technology infrastructure and provider relationships. Navigating that landscape without a clear positioning is increasingly difficult.

Private cloud is not the safe harbour it looks like at first glance

IDC commonly emphasizes that private cloud is the ultimate sovereign cloud, and this remains strongly the case as very few companies wish to exit all their datacenters and move wholesale to the public cloud. As adoption of private cloud has grown and evolved, it has moved from bespoke private cloud implementations towards being built on end-to-end private cloud stacks from major providers, with popular options being Microsoft Azure Local, Google Distributed Cloud, AWS Outposts, or VMware Cloud Foundation. This has resulted in unprecedented capability for enterprises running their own applications and services – but with this has also come a co-dependency on external providers for the ongoing operations of the control plane of the private cloud.

Should any serious technology or political issues arise that interrupts the connection between the public cloud based control plane and the private cloud, services deployed and delivered on the private cloud infrastructure may remain static, degrade over time, or even stop working. The end result is a bought and paid for sovereign physical infrastructure that is unable to operate effectively due to a non-sovereign operations management dependency – and this is a major risk today that a few years ago seemed unthinkable.

European customers have been providing forceful feedback to private cloud stack providers that this public cloud control plane dependency is untenable, and the market is beginning to respond. Most, but not all, providers of private cloud stacks have begun to offer an on-premises approach to the control plane, allowing fully disconnected management of applications or digital services deployment and operations, as well as of licencing tracking and billing, or updates and patching from offline sources.  The big challenge though is that these disconnected options are often limited when it comes to go to market, with vendors limiting access to the largest companies or critical national infrastructure providers or the defense industrial complex. While this may be acceptable initially as solutions come to market and are proven, for the longer-term vendors will need to make disconnected operations a core part of their value proposition across the whole customer base.

AI sovereignty: the new frontier

AI sovereignty has been part of the digital sovereignty debate for some time. But it has now emerged as the new frontier: the question of who controls the models, the data used to train them, and the inference infrastructure is becoming as contested as data residency was five years ago. The general read in the room: AI sovereignty is harder to achieve than data or infrastructure sovereignty, and the messaging across the industry remains inconsistent.

Dig deeper into the research

The dinner was one part of a broader IDC programme on digital sovereignty across Europe. If the themes above are relevant to your positioning or go-to-market strategy, here is where to go next.

Digital Sovereignty Beyond the Label – IDC’s Strategic Guide cuts through the definitional noise and explains what buyers actually evaluate when assessing sovereign solutions and providers. Download free.

From Sovereignty Claims to Credible Positioning – A customer case study on how technology providers are turning sovereignty into a commercially viable proposition. No form required.

Missed the webinar? Rahiel Nasir and Duncan Brown covered buyer expectations, sovereign washing, and practical go-to-market guidance on June 18. The on-demand recording is available here.

IDC’s Digital Sovereignty research covers cloud strategy, data governance, regulatory compliance, and infrastructure sovereignty across European markets. Research presented at the dinner was drawn from IDC’s European Digital Sovereignty Survey and the Semiannual Public Cloud Services Tracker.

Rahiel Nasir

Rahiel Nasir - Research Director, Cloud and Infrastructure Services

Analyst Profile
Rahiel Nasir is Research Director within IDC’s enterprise infrastructure global research domain and part of the cloud and infrastructure services subdomain. He leads IDC's Digital and Cloud Sovereignty research and contributes to IDC’s research on European Cloud adoption trends and…
Andrew Buss

Andrew Buss - Senior Research Director, Digital and Datacenter Infrastructure and Services

Analyst Profile
Andrew Buss is Senior Research Director within IDC’s enterprise infrastructure global research domain. He covers Datacenter Infrastructure Services as part of the Digital and Datacenter Infrastructure Strategies subdomain. Andy’s research focuses on datacenter facilities owned and operated by service providers,…
Duncan Brown

Duncan Brown - Group Vice President, Worldwide Security Products, Worldwide Sustainability

Analyst Profile
Duncan Brown leads IDC’s worldwide security products research, covering endpoint, network, identity, cloud, application security. His analysis and opinions on security, cyber-resiliency, sovereignty and AI governance are widely sought by industry leaders and investors, while his comments on industry trends…

In two earlier posts I argued that SaaS is being disrupted rather than killed, and that the per-seat revenue model is on its way out. The dramatic decline in market capitalization of SaaS vendors over the past 9 months, sometimes referred to as the SaaS-pocalypse, is partly about investors pricing in the fear that SaaS applications will recede behind an AI agent layer. This would make the SaaS applications become invisible “featureware,” with the agent capturing the user relationship, the workflow, and, eventually, the budget. 

This post will show that enterprise buyers now expect their software vendors to supply the agents, and to serve as the trusted source of data and context for custom-built and third-party agents. This is the natural next progression for SaaS vendors and represents an attractive market opportunity. 

To avoid confusion, here are IDC’s AI-related definitions. An AI assistant is conversational and works as a tool for a human. An AI agent is autonomous, uses other tools, and carries memory and context across tasks. An agentic workflow is a business process that an agent executes end-to-end with limited human intervention. 

SaaS vendors are faced with a dual threat, hence SaaS-pocalypse 

The first threat is that organizations will simply write their own applications instead of buying standard SaaS applications. This threat triggered the dramatic devaluation of SaaS stock in February as Anthropic released its Code capabilities. Conversations with CIOs in enterprises partly validate this fear. While they are not contemplating creating core accounting, HRIS or workforce management applications, they might build rather than buy auxiliary applications in areas such as planning, performance management, compensation management, logistics planning, etc. Application areas where customer requirements vary widely and where legal complexity is low are moving gradually from buy to build. 

The second threat is that agentic overlays will increasingly handle the user interaction while AI agents access SaaS applications via API interfaces to carry out transactions on behalf of the human user. The implication is key price justifiers of SaaS applications, such as the interface, the feature breadth, and the brand gradually disappears from the users. This also implies that the per-seat user pricing stop making sense, when humans are no longer the primary users of SaaS applications. 

AI agent adoption is already past the tipping point 

In IDC’s April 2026 Future Enterprise Resiliency and Spending survey of organizations with 500 or more employees, 74% had already deployed at least one agent, 15% were piloting, and only 1% reported no use and no plans. The same respondents expect the number of agent types in production to roughly triple, from 24 in March 2026 to 62 by 2027. Buyers are not evaluating whether to enter the agentic era. They are deciding which parts of their operation to hand over first, and operational and core business data are their top target. 

The big question is who will deliver these AI agents. Most organizations have deployed standard AI tools and run pilots, but few have redesigned core processes to use AI at scale. The survey results shows that most organizations deploy ready-made agents wherever they can, rather than build their own. 

Where vendor-supplied agents win 

IDC distinguishes four kinds of agent by who builds them and how the buyer obtains them. In-application agents come packaged inside the application and the buyer simply adopts them. Low-code / no-code agents are configured by the buyer in a visual builder the vendor provides. Standalone agents are third-party products the buyer implements alongside existing applications. Custom-built agents are assembled by internal teams using full-stack orchestration frameworks. 

The survey data, which focuses on AI agent quantities as opposed to spend, points in one direction. The two types that vendors supply directly, in-application agents and low-code or no-code builders, are growing fastest in numbers and from the largest installed base. Custom-built agents show the slowest growth, because the orchestration they require is more difficult and require more inhouse skills to build. Buyers prefer to adopt or configure an agent that already understands their data and respects their permissions over building one from scratch. 

SaaS applications as trusted data and context for custom-built agents 

IDC also sees massive demand for custom-built AI agents, especially for core business processes unique to an industry or organization. Standalone products and custom-built agents will operate inside the same enterprise, and they will need data and context that lives inside your application. 

A custom-built or third-party agent that accesses data “from anywhere” still needs a place where the data is correct, the process is compliant, the permissions are enforced, and the transaction is guaranteed to execute. A SaaS vendor can offer vetted business processes, governed data, and audit trails for custom AI agent consumption. This is, in IDC’s view, a key future role for today’s SaaS applications. 

What the AI-pivoted SaaS application looks like 

The interface stops being a single screen and becomes several modes serving the same processes: the traditional UI, a conversational UI, a flow-of-work UI embedded where the user already operates, and machine interfaces so external agents can call the application directly and safely. 

The AI-pivot requires SaaS vendors to rethink the workflow from the ground up, which touches the full stack: foundation models, an embedding layer, a vector database, retrieval-augmented generation, an orchestration layer, guardrails, monitoring, and version management. The vendor also has to give buyers an agent toolkit of their own, so that the low-code and no-code configuration buyers increasingly demand happens inside the vendor’s governed environment rather than outside it. 

European vendors carry an additional set of requirements that, handled well, become a selling advantage. Compliance with GDPR, NIS2, and the EU AI Act (still there despite the recent delay), data residency and sovereign cloud guarantees, genuine multi-language model performance, and transparency in how the AI reaches a decision are all conditions of sale to compliance-sensitive European buyers. 

SaaS is not dead, and the incumbents are not doomed. But the asset that justifies a vendor’s existence is shifting from the screen the user looks at to the agents the vendor supplies and the governed data those and other agents rely on. Your customers already expect you to be their agent supplier. The only question is whether you are ahead of that shift or reacting to it. 

So, what do you actually do with this? There are three concrete moves software vendors need to make in the near term. They are specific, they are sequenced, and the window to move first is closing. I will walk through all three in a focused 25-minute webcast, grounded in IDC survey data from more than 1,000 enterprise organisations: where your customers sit on the AI maturity curve, why vendor-supplied agents will dominate enterprise deployments through 2030, and which ERP and SaaS processes are attracting the most AI investment right now. Secure your spot here. 

Bo Lykkegaard

Bo Lykkegaard - Associate VP for Software Research Europe

Analyst Profile
Bo Lykkegaard is associate vice president for the enterprise-software-related expertise centers in Europe. His team focuses on the $172 billion European software market, specifically on business applications, customer experience, business analytics, and artificial intelligence. Specific research areas include market analysis,…

Last week, a select group of senior print and imaging executives gathered in London for IDC’s Print and Imaging Leadership Dinner. During this invitation-only evening, a conversation unfolded between IDC analysts and the people shaping the industry, moderated by IDC’s Sandra Ng.  

What came out of that dinner? Some of the discussions reaffirmed what many already suspected. But some of the insights revealed will fundamentally change how forward-thinking vendors approach the next 18 months. Here’s a taste of what was discussed, and why you’ll want to be in the room for one of IDC’s executive dinners next time.  

The buying committee has expanded, and most vendors are still selling to the wrong people  

Two years ago, a print deal sat with IT and procurement. That’s no longer the world we’re operating in. IDC’s 2026 European Print Survey, covering 2,000 organisations across eight markets, revealed that the stakeholder landscape has shifted dramatically. The conversation that used to happen in one room now happens in four.  

The implications for how vendors structure their go-to-market approach are significant, and the dinner surfaced a very specific playbook that the those gaining the most ground are already executing. We’ll leave the details for the briefing room.  

Security just overtook cost reduction as the #1 investment driver in print. 

A striking 24% of European technology buyers now cite security and compliance as their primary reason for investing in print. That puts it ahead of both cost reduction and productivity.  

This is more than a repositioning opportunity, as it moves the conversation to a different level within the organization,  with a different buyer. Those in the room heard exactly which messaging reaches the CISO, which regulatory triggers are opening budgets right now, and where the hardware story needs to evolve to stay relevant.  

IDC predicts that 40% of worldwide new office MFP shipments will be classified as AI MFPs by 2027. The vendors with a credible roadmap published today will be the ones with a strategic seat in 24 months. Those without one are already behind.  

The buyer has already formed a view before your sales team picks up the phone  

This was the session’s sharpest insight, and the one most likely to keep vendor CMOs up at night.  

GenAI-sourced web traffic grew 1,200% between 2024 and 2025. Two in three searches today end without a single click. Buyers are shortlisting vendors, forming preferences, and making preliminary decisions inside AI assistants, before they’ve seen your website, opened your brochure, or taken a sales call.  

IDC’s Gala Spasova gave a demonstration that stopped the room. When major AI assistants were asked the questions a head of digital workplace would actually type, around 30 vendor names came back consistently. Not a single print OEM appeared. When the question became print-specific, all the familiar names showed up.  

The print category is owned. The workplace category, where your buyers are actually looking, is invisible.  

What it takes to change that, and how fast it compounds once you do, was laid out in detail at the dinner. The short version: it’s not pay-to-play, and the window to act is narrow.  

Three places the money is actually moving in 2026, and the 12–18 month window you can’t afford to miss  

IDC analysts Jacqui Hendriks and Gala Spasova mapped out three near-term growth areas where European buyer investment is already building, from value-add software and services through to Intelligent Document Processing and a sustainability play that changes both the buyer and the budget.  

The most time-sensitive of these? A three-way alliance opportunity, vendor, channel, certified refurbisher, that’s unserved by the larger SIs and telcos, but not for long. European refurbished device shipments grew 28% in 2025. Demand is running well ahead of vendor readiness. The potential of such a model was discussed at the dinner in some detail.  

The commercial model shift that separates the winners  

The evening closed with a discussion on what’s actually different about the vendors capturing European growth. It’s not just what they’re selling. It’s the contracts they’re willing to sign, the conversations they’re prepared to have, and the partnerships they’re building now.  

Roberto Alunni and Phil Sargeant laid out, with uncomfortable precision, the behaviours that distinguish vendors gaining ground from those defending yesterday’s revenue. Some of it is replicable quickly. Some of it takes 18 months of investment to build. All of it was on the table.  

Were you in the room?  

If you weren’t at IDC’s Print & Imaging Leadership Dinner, or if you’re wondering how to get on the guest list for the next executive dinner, now is the time to reach out. Events like this are where the defining conversations happen: the information and insight that doesn’t make it into LLMs and the strategic debates that shape how the market moves, alongside networking and the connections that open doors.  

Whether your focus is European print and imaging, AI-driven workplace transformation, digital sovereignty, channel partnerships, or any of the many other topics shaping the European technology landscape, IDC brings together the senior leaders and the research to drive the conversation forward.  

To find out more about IDC’s European print and imaging research programme, or to join the conversation at our next event, contact your IDC representative or simply fill in our contact form.  

IDC’s European print and imaging research covers 2,000 organisations across Czech Republic, France, Germany, Italy, Poland, Spain, the UK and the Nordics, across 15 verticals. The 2026 European Print Survey data underpinning this dinner is available to IDC clients and select briefing participants.  

Phil Sargeant

Phil Sargeant - Senior Program Director, Imaging and Hardcopy Devices and Document Solutions, European Region

Analyst Profile
Phil Sargeant is IDC’s leading expert in the field of imaging, hardware devices and document solutions. As senior program director, he researches and reports on the key aspects of the multifunction, production and large format printer markets and is also…
Gala Spasova

Gala Spasova - Senior Research Manager, Europe Smart Office and EMEA Content & Knowledge Management Strategies

Analyst Profile
Gala Spasova is a senior research manager in IDC's Future of Workplace & Imaging team. Her research focus is on Hybrid working, Smart Office technology and Content & Knowledge Management Strategies in EMEA.  Spasova is also part of the European…
Jacqui Hendriks

Jacqui Hendriks - Associate Research Director, European Print Vendor Transformation Strategies

Analyst Profile
Jacqui Hendriks, Associate Research Director, European Imaging, Printing and Document Solutions Jacqui Hendriks heads up IDC's European Print Vendor Transformation Strategies research program, in collaboration with various IDC research domains. Hendriks has more than 30 years of experience of working…
Roberto Alunni

Roberto Alunni - Senior Research Director, EMEA Data & Analytics

Analyst Profile
Roberto Alunni is a Senior Research Director at IDC for imaging, print, and document solutions research across the EMEA region. He is responsible for strategic and operational implementation and leads an international analyst team. He is a specialist in imaging…
Sandra Ng

Sandra Ng - Senior Vice President, WW and APJ Research

Analyst Profile
Sandra Ng is Senior Vice President at IDC and the Global Domain Leader for Devices, Consumers, Imaging, and Japan. Based in Singapore, she advises technology buyers and vendors worldwide on technology investments, financial priorities, and go-to-market strategies. She leads a…

Artificial intelligence has been part of the telecom conversation for years. What is changing now is its role and scale. 

AI is no longer limited to isolated use cases or innovation initiatives. It is increasingly influencing core infrastructure decisions, from data center strategy to network architecture and investment priorities. 

Across EMEA, telcos are moving from experimentation to more structured, large-scale adoption. 

AI investment in telecommunications is accelerating across EMEA 

AI and generative AI spending in telecommunications is growing rapidly. In EMEA, spending is expected to increase at a compound annual growth rate of 31.8% between 2024 and 2029. 

Most telcos are already using, or planning to use, AI and machine learning to optimize network operations, improve customer experience, and explore new revenue streams. 

At the same time, operators are becoming more pragmatic. There is increasing focus on aligning AI ambitions with what existing data, cloud, and operational capabilities can realistically support. 

AI is reshaping telco infrastructure priorities 

As AI adoption scales, it is beginning to reshape how telcos think about infrastructure. 

Data center investments are being driven by workloads such as AI inferencing and large language model training. These require high-performance, low-latency environments and are pushing telcos to rethink how compute, storage, and networking are designed and deployed. 

This is reflected in several shifts: 

  • Closer collaboration with hyperscalers and ecosystem partners  
  • Expansion of colocation and edge deployments  
  • Greater focus on GPU-intensive infrastructure  

Infrastructure is becoming more closely aligned with the need to support real-time, distributed AI workloads. 

How short-term ROI is shaping AI adoption in telecom 

While investment is increasing, telcos are prioritizing use cases that can deliver measurable value in the near term. 

Employee productivity, customer experience, automation, and operational efficiency are key focus areas. These areas offer clearer paths to return on investment compared to more experimental AI initiatives. 

This creates a balance between near-term impact and longer-term transformation goals, such as autonomous networks and more adaptive service models. 

Data and cloud foundations remain a key challenge for AI 

Despite strong momentum, many telcos are still working to align their underlying capabilities with AI ambitions. Strong security and data privacy protections are fundamental to ongoing telecom investment in AI capabilities. If a capability or vendor partner is not trusted it won’t be implemented in production. 

Challenges around data quality, data management, and cloud readiness can also practically limit the speed and scale of AI adoption. As a result, AI strategy is closely linked to broader transformation efforts, including modernization of data platforms and investment in hybrid infrastructure. AI capabilities often act as multipliers of existing capabilities. The better the foundation the greater the impact and ability to scale. 

What this means for telecom operators 

AI is becoming a cross-functional priority that connects network, IT, and business strategy. 

Infrastructure planning, partner selection, and operating models increasingly need to reflect AI requirements. At the same time, telcos are working more closely with partners to access capabilities, accelerate adoption, and manage complexity. 

As AI becomes more embedded, it is also influencing how services are designed and delivered, and how operators position themselves in the market. 

Download the full analysis 

AI is one of the defining trends shaping the telecom market. In the IDC eBook State of the Telco Market 2026, you’ll find detailed data, forecasts, and analysis on how AI investment, infrastructure, and operating models are evolving. 

Download the eBook to explore the data behind these developments and better understand how the telco landscape is changing. 

If you’re currently evaluating how AI will impact your infrastructure, operations, or partner strategy, our experts are happy to exchange perspectives. Whether you’re at an early stage or already scaling initiatives, we welcome the conversation. Get in touch with our team to continue the discussion. 

Chris Silberberg

Chris Silberberg - Research Manager, Global Telecom Operations and Monetization

Analyst Profile
Chris Silberberg is Research Manager for IDC’s global Telecom Operations and Monetization research. Chris’ core research coverage includes the evolution of telco monetization, customer experience, orchestration, and assurance capabilities. Telcos are at a crossroads, double down as utility providers or…

Most EMEA organisations have the intent to scale AI. What they are missing is a way to execute. On May 28, 2026, IDC’s EMEA Digital Leaders Hub brought together Martina Longo, Daniel Saroff, and Giulia Carosella for a live session drawing on 12 months of conversations within the Hub and fresh IDC research. Below is a brief overview. The full recording is available on demand. 

AI maturity in EMEA in 2026: why execution, not intent, is the real gap 

IDC’s latest MaturityScape Benchmark (EMEA, N=583) tells a clear story: 63% of EMEA organisations are still in the two lowest AI maturity stages. Fourteen percent are ad hoc: scattered initiatives, no coherent strategy. Forty-nine percent are opportunistic, running pilots but without the repeatability needed to scale. Just 2% are effectively scaling AI and Agentic AI initiatives across their organizations, including unlocking AI-driven revenue growth. 

The journey maps from the (Gen)AI Scramble (fragmented, investment-heavy experimentation) through the AI Pivot (structured scaling) to the Agentic Organisation (AI embedded across operations). Most EMEA organisations are stuck in the transition between the first and second stage. The blocker is almost never ambition. It is the ability to execute. 

Why AI adoption in EMEA is stalling: five challenges organisations need to address 

Notably, 49% of EMEA organisations have already shifted their focus from launching new AI pilots to improving existing initiatives The experimentation phase is peaking, and EMEA organizations are no longer seeking new tools but instead focusing on making current AI work effectively first. But five structural challenges continue to slow progress: 

  • Competition for resources among digital initiatives 
  • Regulatory uncertainty slowing deployment decisions 
  • Resistance to process change within the business 
  • Difficulty quantifying and demonstrating AI ROI to the board 
  • Lack of executive sponsorship or organisation-wide buy-in 

These are not isolated problems. They compound each other. Without a shared language for value, the resource conversation is difficult to win. The webinar addressed all five, and the one that generated the most discussion was ROI. 

Measuring AI ROI: why cost savings are not enough 

The most common reason AI initiatives stall is not technical. It is that no one agreed upfront on what success looks like. IDC’s AI Business Value Benefit framework maps nine dimensions where AI creates measurable impact, spanning Revenue Generation and Customer Experience through to Sustainability, Time to Market, and Business Resilience. Most organisations are measuring only one or two of these dimensions and are therefore systematically underselling the value they already have. 

“Know what you want to achieve and how you will measure it” 
  — Alex Catmur, Commercial Director Digital, AtkinsRéalis 

Three practices that came up consistently in the session: 

  • anchor every initiative to a specific business outcome before selecting any tool: Start with value drivers, not technology 
  • if no executive has a stake in the metric, the initiative will eventually stall: Align to KPIs executives already own 
  • productivity gains are visible; resilience and trust are harder to quantify but equally real, and the framework accounts for both: Separate direct and indirect value 

The session also walked through a detailed case study of a global professional services firm that went from no shared ROI lens to confident scale decisions. If that is where your organisation is at present, it is worth watching the recording to hear how they structured the turnaround. 

How the CIO role is evolving in the age of AI 

IDC’s WW C-Suite Tech Survey (EMEA, N=300) makes the expectation clear: 42% of the broader C-suite now expects the CIO to lead digital and AI transformation with a major focus on creating new revenue streams. That expectation is growing faster than the formal authority that would make it achievable. 

The digital leader of the future, as IDC frames it, is an architect of three things: Workforce (orchestrating AI-fuelled change management), Resilience (modernising IT for strategic alignment), and Value (demonstrating what digital technologies actually deliver for the business). 

Three steps for digital leaders looking to prepare for this shift: 

  • not called in to implement choices that have already been taken: Get in the room before decisions are made 
  • accountability for results, not just go-live dates: Own the business outcome, not just the delivery 
  • design AI deployments to grow and withstand failure, not just to ship: Architect for scaling and recovery from the start 

The session went into considerably more detail on each of these steps, including the structural and political dynamics that make them harder in practice than they appear on paper. 

A practical AI transformation playbook: four steps that matter

The session closed with a synthesis that cuts through the complexity. Leading AI-fuelled business transformation comes down to four sequential actions: 

  • modernise architecture and data before scaling AI; pilots built on brittle infrastructure do not survive production: Fix the foundation 
  • anchor every initiative to a KPI an executive already owns; no metric, no mandate: Define the value 
  • redesign workflows and roles alongside the technology; AI layered onto old processes delivers expensive old results: Change the model 
  • run experiments to disprove bad assumptions quickly; promote only what survives to a funded pilot with a scale plan: Scale what works 

Straightforward to state, harder to execute. The webinar covers what this looks like in practice, including the Q&A that followed. 

► Watch the full recording on demand 
 

The complete recording covers the full AI Business Value Benefit framework across all nine dimensions, the case study of a professional services firm moving from pilot to scale, the detailed best practice sessions on ROI measurement and the evolving CIO mandate, and the Q&A with the IDC analysts. If the topics covered are relevant to your organisation’s AI journey, IDC’s EMEA Digital Leaders Hub offers advisory support, benchmarks, and peer roundtables for CIOs and digital leaders navigating this transition. Reach out via the contact form to continue the conversation. 

Martina Longo

Martina Longo - Research Manager, CIO and CTO Buyer Insights

Analyst Profile
Martina Longo is a Research Manager for the CIO and CTO Buyer Insights program. Her research focuses on the emerging priorities, programs and decision making processes linked to the modern CIO/CTO agenda. This includes advancing AI from experimentation to operational…
Daniel Saroff

Daniel Saroff - Group Vice President Research and Consulting

Analyst Profile
  Daniel Saroff is Group Vice President of Research and Consulting at IDC, where he leads the research agenda focused on end-user technology leaders, including CIOs and their direct leadership teams. He oversees a team of analysts and advisory professionals…
Giulia Carosella

Giulia Carosella - Senior Research Manager

Analyst Profile
Giulia Carosella is a Senior Research Manager in IDC's AI-Fueled Business Strategies team, leading the Worldwide research program. In this role, she researches current and emerging global trends in AI?driven business transformation, examining how organizations can reinvent themselves by leveraging…