AI Business
How AI is really impacting the EMEA IT Channel: Insights from the GTDC Summit
How AI is really impacting the EMEA IT Channel: Insights from the GTDC Summit
By Richard Sapsed, Head of sami at CI Group
Last week I attended the GTDC Summit EMEA 2026 in Noordwijk, one of the most important gatherings of senior technology distribution executives in the calendar. This year’s theme was Empowering the Digital Evolution, and if there was any doubt that AI would dominate the agenda, it was dispelled within the first hour.
AI is currently everywhere in the channel: in vendor go-to-market strategies, in distributor operations, in reseller conversations with end customers, and increasingly in the regulatory frameworks governing how all of those businesses operate. The real questions, and the ones I heard repeated throughout the two days, are more granular: how do we build genuine capability, how do we use it responsibly, and how do we make it work commercially across a partner ecosystem?
I joined a panel of senior industry leaders for a session titled ‘How is AI Really Impacting the EMEA IT Channel?’ What follows draws on what I shared there, and provides some of that clarity to channel leaders navigating the same questions.
How AI is changing channel marketing
AI is changing channel marketing in three concrete ways: speed, personalisation, and precision. It compresses the time required to build campaigns and localise messaging. It makes content tailored to different partner types achievable at scale without a proportional increase in headcount. And it enables insight-driven decision-making rather than campaign-driven activity.
The important caveat: AI amplifies whatever is already true in your strategy. If the fundamentals are weak, AI will scale the mess faster. If the basics are solid, it can be a powerful multiplier.
AI as a strategic tool, never a shortcut
The way I encourage channel leaders to think about their relationship with AI is this. It should function as a thought partner, a productivity accelerator, and a learning tool. For channel businesses operating across multiple vendor lines, partner tiers, and geographies, that last capability alone is significant.
But AI does not replace judgement. It handles the heavy lifting of synthesis and drafting, but the responsibility for nuance, accuracy, and decision-making remains with the person using it. Channel leaders who treat AI as a decision-maker will find themselves in difficulty. Those who treat it as a tool will find themselves with a meaningful competitive advantage.
What mature AI adoption looks like in a channel business
Most channel businesses will recognise the early stage: people using AI informally to save time, creating inconsistency and risk. The more deliberate phase focuses on use cases with demonstrable returns: content development, knowledge retrieval, and workflow automation.
The shift that separates organisations genuinely benefiting from those still experimenting is strategic. AI stops being a side tool and becomes part of the core operating model. The question changes from ‘what can AI do?’ to ‘which of our business processes can be redesigned to leverage AI effectively?’ That redesign mindset is where the real value is created.
What effective AI training looks like
AI capability-building needs to happen at three distinct layers, and most businesses are only investing in one of them.
Basic literacy ensures everyone understands what AI can and cannot do. Role-based enablement gives specific teams the skills to use AI in the context of their actual work. A marketing team’s AI needs are different from a sales team’s working across a distribution model. The third layer, most often neglected, is leadership. Senior leaders must understand not just the tools, but the governance implications and investment priorities. The EU AI Act has made AI literacy a core requirement for responsible deployment, and that expectation reaches into the boardroom.
The most valuable skill is not knowing how to use a specific tool. It is knowing how to evaluate AI outputs, and to recognise where the technology excels and where human expertise remains irreplaceable.
Governance: the right frame
Channel businesses often approach AI governance as a barrier. I would encourage a different frame. Clear guidelines on what data can go into public models, and which outputs require human review, are not restrictions on adoption. They are the conditions that make responsible adoption possible at scale.
In a channel context, this also means being deliberate about which tools are appropriate for which tasks, rather than allowing an uncontrolled patchwork of individual choices to develop across the business. Build these guardrails early and they become an enabler. Retrofit them later and they become expensive.
The EU AI Act: what channel businesses need to understand now
The intent of the EU AI Act is sound: to make AI safer, more trustworthy, and human-centric while still supporting innovation. In practice, it is accelerating conversations about transparency, model accountability, and risk management that channel businesses should have been having already.
Most channel organisations are not building frontier models. But procurement conversations have changed, vendor due diligence has changed, and for businesses operating in the EU market, the compliance requirements are present now, not a future consideration. For smaller channel businesses, the risk is that the compliance overhead becomes disproportionate. The practical challenge is staying compliant without allowing that burden to crowd out the innovation that makes AI valuable.
Six things channel leaders should do in the next twelve months
Start with business problems, not tools. Ask where you are losing time, quality, or insight, and let that drive tool selection.
Pick high-value use cases for early wins. A well-chosen early success builds organisational confidence faster than a grand strategy document.
Invest in AI literacy as a broad capability, not a technical one. Businesses that keep AI understanding inside the IT function will be overtaken by those that distribute it across marketing, sales, and operations.
Embed governance early. Legal, security, and compliance need to be in the conversation from the outset, not retrofitted later.
Keep a human in the loop. AI is powerful, but human judgement remains irreplaceable in client-facing decisions, partner relationships, and anything with significant commercial consequence.
Treat AI as a capability shift, not a software purchase. The real value comes from how it changes the way your teams work and the quality of decisions they make.
