With AI seemingly having an impact on every part of our lives now, how are resellers introducing generative or augmented intelligence to the solutions they offer?
AI adoption has shifted from experimentation to practical, strategic application. Businesses now focus on clear returns, security, and cross-functional integration across departments like sales and customer service. To succeed, channel partners must act as “customer zero,” adopting AI internally to build credibility before advising clients.
It’s a topic that needs no introduction. Whether it be new capabilities, its impact on the stock market, or one of the tech giants buying a new start-up, artificial intelligence has been dominating headlines in every sector for years now.
With Nvidia announcing a financial year in which they made $200 billion in revenue, and the rest of the ‘Big Tech’ companies committing to $660 billion of investment in AI, we might be able to land on 2026 being “the year of AI.”
While these numbers are, frankly, ridiculous, they represent a fact that AI is real and something that businesses need to pay attention to.
“The AI conversation has clearly moved from experimentation to practical application,” said Oliver Harvey-Jones, Cloud Director UK&I at Arrow ECS. “Businesses are no longer asking whether AI is relevant and are focused on how to apply it in a structured and responsible way.”
But with so much noise around the subject, how businesses apply AI is a conversation that needs to be had. Yet with the current commentary, you’d be forgiven for assuming businesses had either already adopted AI or were scared of it.
“How AI is often portrayed is either it is fantastic, it’s going to solve world hunger, and it’s extremely powerful, or it doesn’t work, or it’s extremely dangerous,” said Peter van der Putten, Director of the AI lab at Pega. “The truth is more in the middle.”
“There are particular pockets where you see a lot of adoption, and there are particular companies that go a bit faster and others that take a more step-by-step approach.
“Businesses are still excited about AI, but they’re a lot more grounded about it than they were a year ago,” said Eduardo Mota, Senior Cloud AI Architect. “GenAI isn’t a shiny new toy for businesses anymore.
“There’s definitely still a strong appetite to adopt it, but businesses have a different focus now. A lot of the interest is in practical use cases, notably in back-office functions, and running smaller, lower-cost models that are easier to manage and more likely to show a clear return.
“Overall, the mood is still positive, albeit more disciplined. Businesses see the potential, but they know it takes the right data, the guardrails and pace to make it worthwhile.”
While the mood is positive, Mota added that businesses are also aware of the cost implications of building the right solution for them, rather than adopting a ‘one-size-fits-all’ solution.
As Harvey-Jones points out, organisations are now looking for bespoke solutions, ticking off questions around security, compliance and adaptability before diving into an AI solution.
“What we are seeing is that organisations gaining the most traction are approaching AI strategically rather than tactically.
“Generative AI, particularly through tools such as Copilot, is beginning to reshape how employees interact with data, automate workflows and improve productivity. However, successful adoption extends beyond technology. It involves governance, security and, importantly, change management.”
The Exciting Stuff
While every investor who’s just dumped their holding of Monday.com or Workday is talking of what AI will be able to do in the future, many businesses will be asking, ‘What can it do now?’
Those who have been in the tech industry for some time, like van der Putten, will argue that ‘AI’ has “been around for 20 or 30 years now”, but the difference is how we are interacting with it.
“Traditionally, AI was applied a lot in data interactions or process-heavy use cases. If you have a lot of data, you can use AI, but there also needs to be a need for it. If you have lots of customer interactions, for example, these are repeatable processes where you need to make smart decisions, it makes sense to plug in AI.”
“AI innovation is cross-functional,” added Harvey-Jones. “Rather than being confined to IT, it is becoming embedded across sales, marketing, finance, operations and leadership teams.
“Through tools such as Copilot, sales teams can accelerate proposal development and end- customer follow-up, marketing teams can streamline content creation and campaign analysis, and finance teams can enhance forecasting and reporting accuracy.
“The impact is not simply speed; it is also consistency, insight, and improved decision-making. From an operational perspective, platforms supported by AI capabilities enable channel partners to analyse data more efficiently, surface insights and respond more quickly to end-customer needs. The efficiencies delivered are measurable, such as reduced administrative overhead, faster time to insight, and improved end-customer engagement.
“Importantly, the greatest success comes when AI adoption is practical and role-specific.
When teams understand how AI supports their day-to-day responsibilities, value naturally increases.”
EG of AI
The contact centre is a great example of where day-to-day responsibilities have been supported by artificial intelligence. Since the introduction of AI, call times are shorter, interactions are better, and agents can provide a personalised experience, leading to higher overall satisfaction.
Those in charge of the customer experience may want to summarise what’s been discussed in a particular call. According to van der Putten, “in some more advanced use cases, Agentic AI can be used to provide a lot of the customer service experience on autopilot” with the call centre backing up the AI.
“The customer service rep is coached through the interaction with these intelligent agents through a customer desktop so the agent is almost on autopilot. They can just guide the process more, as opposed to having to drive it.
“If that does a good job, then businesses can also use it in self-service, where the analytical AI comes back into play to predict customer service issues before they happen.”
Serving Customer Zero
While the contact centre is already experiencing some of the advantages that AI can bring, for the reseller, the common thread of advice is to use AI within your own organisation before trying to sell it to the customers.
“The channel partners who are making the most progress are those acting as ‘customer zero’ – adopting AI internally, understanding its impact firsthand, and then using that experience to guide end-customers,” said Harvey-Jones. “That internal adoption builds credibility and enables more informed, outcome-focused conversations.
“Resellers can demonstrate leadership by embedding AI into their own operational processes before positioning it externally. When channel partners use AI internally, they move beyond theoretical discussion to practical experience.”
“Some of the major opportunities for cloud resellers are both internal, for example, within their own sales department and operations, as well as external, with AI-led value propositions they bring to their clients” added Van der Putten.
“Internally, for instance, in our own company, we have our own internal sales automation applications that we sell to our customers. Lead scoring, finding opportunities, planning meetings, figuring out what to focus on, and how to move deals to the next stage.
Our sales automation applications internally and externally are heavily AI-led because you don’t have the luxury of a handful of salespeople who are stars and the rest are not performing.”
Van der Putten finished by adding that resellers need to avoid falling into the trap of becoming an AI consultancy if they want a repeatable business.
“Externally, resellers should think about what they can add on top of their value proposition. If we use the hyperscalers as a commodity but add some applications, vendors, services that are just one layer above in this AI application layer, as opposed to underlying foundation models or underlying AI services.
“I think that’s an opportunity for resellers to think about what they can offer more in that application layer. Take the services of the companies that are doing Agentic AI or provide an AI governance layer, or a responsible AI layer on top of it.
“Intelligence sounds useful, but if you can’t put it into a process, it’s going to be pretty useless. So use vendors that have strong process or workflow capabilities that you can plug the AI into.”
