The channel’s biggest AI opportunity is fixing what customers already have

AI continues to dominate conversations across the technology industry. Every week seems to bring a new model, platform, or product announcement, alongside predictions about how quickly AI will transform the way organizations operate.

For channel partners, the challenge is deciding where to focus. Customers are looking for guidance, but keeping up with every new development isn't a realistic strategy for most businesses.

What many organizations need right now is more practical. For many customers, the challenge is no longer understanding AI's potential but addressing the data, integration, and operational hurdles that stand in the way of adoption. Information is often spread across disconnected systems, while growing attention to AI costs is increasing demand for more disciplined approaches to deployment and governance.

They are trying to work out how AI fits into their existing technology environment, how it can support day-to-day operations, and how to deliver measurable results. That's where many customers are looking for support - and where partners can have the greatest impact.

Latest Videos From

Watch full video here:

Why promising AI projects get stuck

Over the last few years, organizations have invested heavily in AI pilots and proof-of-concept projects. Many have demonstrated what is possible, but moving from experimentation into wider business use has proven more difficult.

The obstacles are rarely limited to the AI technology itself. Firms often face challenges integrating AI into existing environments, governance requirements continue to evolve, and teams can struggle to connect AI initiatives to clear business priorities. Even when a pilot is successful, scaling it across different teams, processes, and systems introduces a new set of challenges.

Customers need support identifying where AI can make a meaningful difference and how it fits into existing workflows. Just as importantly, they need help addressing the operational issues that can slow adoption long after the pilot phase has ended.

All roads lead to data

For many organizations, progress with AI is constrained by their ability to make data accessible, trusted and usable across the business. Many have accumulated years of information across different applications, cloud environments and departments.

Making that data accessible, reliable and usable remains one of the biggest barriers to successful AI adoption. Half (49%) of UK organizations lack the internal skills needed to integrate AI with existing analytics and business intelligence systems, according to our research. While 37% say gaps in real-time data integration are a major obstacle.

Without a strong data foundation, organizations will struggle to trust AI outputs or apply them consistently across the business.

For partners, this creates opportunities that extend beyond a single deployment. Helping customers improve data quality, connect systems and establish effective governance addresses challenges that continue long after an AI project goes live.

As organizations roll out AI across more areas of the business, these foundations become even more important. This creates ongoing demand for partners that can help customers manage complex data estates, link disparate systems and put the right policies and processes in place.

Complexity isn’t going away

Alongside data challenges, organizations are also managing increasingly complicated technology environments. Few businesses operate within a single vendor ecosystem. Most are working across multiple cloud providers, applications, analytics platforms and AI tools, many of which have been introduced at different stages.

Customers want the flexibility to adopt new technologies without disrupting existing investments. They also want confidence that systems can work together effectively and that today’s decisions will not create unnecessary constraints in the future.

As AI projects move beyond the pilot stage and into wider deployment, organizations will increasingly need support connecting technologies, improving interoperability and reducing operational complexity. Partners that can provide that expertise are likely to become trusted advisors.

Building services customers will continue to need

As AI adoption progresses, some of the strongest opportunities for partners sit in areas where customers will need ongoing support.

Workflow automation is a good example. Many organizations continue to rely on manual processes that slow decision-making, create inefficiencies or make information harder to access. AI can help address these issues, but success depends on understanding how technology, processes and people work together.

The same applies to services focused on AI readiness, data quality, governance and integration, for which there is already demand. UK businesses and IT leaders believe better data integration and analytics would help demonstrate AI's value to stakeholders, while more than half want greater visibility into how AI models reach decisions, our research found.

Organizations are also becoming more disciplined in how they evaluate AI investments. Beyond model performance, there is growing focus on managing operational costs, reducing unnecessary processing, and ensuring that AI systems are working from relevant, trusted data. Strong data practices not only improve outcomes but can also help organizations use AI more efficiently as deployments scale.

These engagements help customers address immediate challenges while creating a stronger foundation for future AI initiatives. They also lend themselves to repeatable service offerings that can be applied across different customers facing similar problems.

The opportunity is already here

For many channel partners, the biggest AI opportunity lies in helping organizations move beyond experimentation and into everyday use.

Many organizations already have the technology required to move forward. What they often need is a clearer path to adoption across the business. Partners that can provide that guidance will be well positioned to strengthen customer relationships and support the next phase of AI deployment.