This article first appeared in News in the Channel magazine issue #41.
There is a rush among many businesses to adopt AI functions, but care needs to be taken to ensure the solutions are right for the business and will deliver the value they seek – and resellers have a vital role to play.
AI functionality has developed at an impressive pace and is increasingly being used by businesses across the spectrum. But in the race to adopt AI, while it can bring benefits, there is a risk that solutions implemented quickly do not deliver the value sought.
Andy Brown, senior business unit director – data, AI and applications, Advanced Solutions, UK and Ireland at TD SYNNEX, says AI can deliver value to every business. “Used intelligently, it will save time and enhance productivity significantly,” he says. “Indeed, this is already happening and businesses that are not already making use of AI risk falling behind competitors who use it to move faster, respond in more targeted ways, and make better use of their time and resources.
But Barb Huelskamp, global VP of Channels and Alliances at SolarWinds, notes that for AI to deliver value, it must be tied to a clear objective. “The organisations seeing the strongest results are using it to solve specific challenges: improving efficiency, reducing repetitive work, strengthening operational resilience, or helping teams make faster, better-informed decisions,” she says.
“AI doesn’t need to be embedded in every process. The real opportunity is identifying where it can make the biggest impact and focusing efforts there. That’s especially true for channel partners, who are often navigating these questions on behalf of their customers at the same time as managing their own operations. When businesses take that targeted approach, AI moves beyond experimentation and starts delivering measurable outcomes.”
David Campbell, product manager of modern workplace at Wavenet, says the question is no longer, ‘Should we try AI?’, but ‘Where does AI fit in our operating model, what problems will it solve, and how do we implement it safely at scale?’
“AI only creates value when it is used confidently, safely and with intent. The AI-ready organisation can point to specific moments in its value chain where AI reliably adds value. That might be drafting first-pass documents with consistent structure, summarising complex meeting notes into actions and owners, extracting themes from service tickets, or turning call transcripts into follow-up plans. For most, AI’s value is acceleration, speeding up thinking, drafting and analysis, while keeping human accountability in place. Get readiness right and the benefits soon start to build, resulting in better quality work, quicker decisions and a more streamlined experience for employees and customers.”
AI for AI’s sake
With the hype surrounding AI, there is a desire from some businesses to not be left behind, but this can lead to applications being deployed because they are AI, not for what they do.
Anthony Dobson, regional director, sales for Arrow’s enterprise computing solutions business in the UK&I, says with AI the starting point must be what the end customer is trying to achieve and where AI can add value to their business.
“In many cases, that comes back to familiar pressures such as improving productivity, reducing manual tasks, making better use of data, supporting teams and improving how services are delivered,” he says. “AI can help in all these areas, but only when it is applied with a clear purpose. It is not about adding AI for the sake of it, but using it to solve a real problem, improve a process or create a better outcome for the end-customer.”
Danny Hemminga, vice president of EMEA partner sales at Tanium, says there’s real pressure to be seen adopting AI quickly, driven by competitive anxiety, board expectations or genuine excitement around what the technology can do. “The risk is that organisations focus on deploying AI rather than on whether the foundations underneath it can actually carry the weight of what they’re asking it to do,” he says.
“The most telling sign of this is when organisations ask ‘which AI tool should we buy?’ before they’ve asked whether their data is accurate, whether their teams have real-time visibility, or whether security and IT are working from the same information. Those fundamentals determine whether AI delivers value or just adds another layer of complexity to an already fragmented environment.”
Nathan Charles, head of customer experience at OryxAlign, agrees that in many organisations, AI has become a boardroom priority and there can be pressure to demonstrate progress when competitors are discussing their own adoption plans.
“That environment can encourage organisations to focus on the capabilities of a particular tool before they have established how it will support existing business objectives,” he says. “A chatbot that answers questions efficiently may attract attention, although the more important consideration is the role it will play once it becomes part of day-to-day operations.
“Organisations are likely to see stronger results when they define the outcome they are trying to achieve at an early stage and use that objective to guide decisions throughout the project.”
Ensuring the right solutions
Resellers play a vital role in helping customers to ensure that customers get the right solutions for their business.
Andy says that AI is raising the bar for what customers think is possible. “They want smarter solutions, personalised interactions and faster responses,” he says. “Partners need to continually adjust their offerings and approach, moving beyond traditional products to AI-driven outcomes that truly solve business problems.
“In addition, AI is becoming more embedded into all kinds of solutions, and partners need to understand the positive impacts that this is having for their customers. They need to comprehend how AI works in tandem with other emerging technologies like cloud, security and networking, to support a more connected, end-to-end approach to digital transformation. This is important as it aligns with how customers buy and deploy technology today.”
Anthony says the most useful conversations are often about readiness. “Data quality, governance, internal processes and end user adoption all influence whether AI will deliver the expected results,” he says.
“Channel partners should be helping end customers understand what foundations are already in place, where there may be gaps and how success will be measured. This is important because it moves AI away from being an experiment and towards becoming a business investment.
“Turning that intent into action is where the right support really matters. At Arrow, we help our channel partners achieve this through initiatives such as our AI accelerator program, giving them the knowledge and confidence to identify opportunities and develop AI services that are grounded in real end-customer needs and the wider business strategy.”
Nathan adds that questions around ownership, employee adoption and operational processes are often just as important as the choice of AI platform. “Even a well-designed solution can struggle if employees don’t understand how to use it or if it doesn’t fit naturally into existing workflows,” he says. “The most successful projects tend to be those where organisations have a clear plan for implementation and ongoing management from the outset.”
Andrew Graham, business development manager at PFU (EMEA) Ltd, says resellers create the most value when they start with the customer’s information and workflows rather than the AI solution itself. “Before discussing models, prompts or applications, they should be asking where information comes from, how it’s captured, how accurate it is and how much manual intervention is currently required,” he says.
“Those factors often determine whether an AI project succeeds or struggles. The reality is that you can upload a handful of documents into an AI platform and achieve reasonable results. Try doing the same with thousands of inconsistent documents and the hidden costs quickly become apparent. That approach is simply not scalable.”
David agrees that organisations need clarity. “To achieve this crystal-clear view, it requires use cases that matter, role-specific enablement and leadership alignment on what ‘good’ looks like,” he says.
“Below the tool, you need strong foundations, including identity and device controls, data classification and protection, role-based access, auditability and a content lifecycle that keeps sensitive information where it should be.
“The difference? It’s not budget. It’s whether the organisation is prepared to make AI useful, safe and dependable. It starts with use cases that matter, it continues with role-based enablement, so people learn how to apply AI in the context of their jobs, i.e. how to prompt, how to validate, how to handle data safely, and when not to use the tool at all. This requires strict governance, with clear policies, escalation routes and accountability.”
Future growth
All commentators agreed that AI adoption will increase. Danny says the conversation is already shifting from excitement to accountability. “The organisations that moved early are now being asked to show what the investment delivered,” he says. “That shift toward measurable outcomes is healthy, and it’s where the real value starts to emerge.
“I expect to see a clearer divide over the next few years between organisations that built AI on solid foundations – real-time data, strong governance, converged IT and security operations – and those that bolted it onto existing complexity. The former will compound their advantage. The latter will find that AI exposed problems they weren’t ready to deal with at that speed.
“The partners that thrive in this environment will be the ones that help customers get the fundamentals right, not the ones that sell the most impressive-sounding AI capability.”
Barb adds that the next phase of AI adoption will be defined less by experimentation and more by execution. “As organisations become more experienced with AI, they’ll raise their expectations,” she explains. “They’ll want to see tangible improvements in efficiency, productivity, customer experience and operational performance. That’s where partners play a critical role – and why having the right training and certifications to stay ahead of the curve matters so much.
“The opportunity isn’t simply helping customers deploy AI. It’s helping them integrate it into everyday operations, navigate governance and security considerations, and ensure it evolves alongside the business. The organisations that see the greatest long-term benefit will be those that treat AI as part of a broader transformation strategy — built on strong processes, clear accountability and a commitment to ongoing optimisation.”
Andrew adds that the conversation is already shifting to AI return on investment. “Organisations are increasingly asking not whether AI works, but why some projects deliver measurable value while others fall short,” he says. “The answer often comes back to information quality. Businesses that invest in capturing, organising and governing information effectively will be far better placed to realise long-term value from AI than those relying on technology alone.”
