Channel partners must focus, stop chasing every tech

Estimated reading time: 5 minutes · Last updated: 10 October 2026

Paul Jackson, Director of EMEA channel at Foxit, argues channel partners should stop trying to keep up with every release and instead specialise where they can deliver ongoing value. He contends partners do better when they focus on select industry verticals, distinct business challenges or targeted technical specialties rather than broad but shallow portfolios. The reasoning is that reliable, repeatable expertise enables a partner to determine if a capability — notably generative AI in document workflows — is suitable, to spot the risks it could introduce, and to plan how adoption should be managed. The page also references a Future Focus 2026 report promoted on the host site.

Why breadth without depth undermines partner value

Many channel conversations start with how partners can keep pace with rapid product change. Paul Jackson rejects the idea that partners should attempt to follow every new feature. He says that a broad catalogue without sustained expertise is difficult to maintain and hard to turn into consistent customer outcomes.

Specialisation can be organised in three practical ways: by industry vertical, by a repeatable business process (for example, HR onboarding or contract lifecycle management), or by a technical domain such as secure document processing. That focus lets a partner build templates, runbooks and governance patterns that shorten delivery time and reduce implementation risk.

The commercial payoff is not only better win rates but more durable revenue. Instead of one-off transactional licensing, specialists can sell adoption, governance and optimisation services that stay relevant after the initial sale because they attend to operational controls and compliance as well as functionality.

How generative AI has changed document-workflow risk

Generative AI moved document-workflow conversations from productivity and licensing into questions of data handling and compliance. Jackson lists the practical concerns organisations now face: where data processed by an AI tool is stored, how long it is retained, whether it is used to train models, who can access it, and how AI tools interact with other business systems.

Those five operational questions convert a technology demonstration into a governance problem. A demo that shows accurate contract summarisation proves capability but does not prove appropriateness. If an AI tool is introduced into an environment with weak access controls or poor record retention, it can surface regulated or sensitive content faster and propagate errors throughout downstream systems.

Partners that can map data flows, identify sensitive fields and specify retention and access controls add far more value than those that only show feature checklists. This is especially important in regulated sectors, though Jackson argues the risk framework should be applied broadly across customers.

Trusted advice requires practical, post-sale support

Jackson sets out a three-part test partners should use before recommending a new capability: first, identify the exact customer problem it will solve; second, assess the additional security, compliance or operational exposures it brings; third, confirm the partner can support responsible adoption after the initial sale.

The third question shifts the sales conversation toward services. Successful AI deployments often require workflow mapping, governance policies, employee training and ongoing performance review. Partners who package those activities create a repeatable services offer that ties revenue to outcomes rather than to a licence transaction.

Jackson suggests that customers frequently want capabilities embedded into existing tools and processes rather than a standalone application. Partners that deliver incremental, measurable improvements — fewer manual invoice touches, faster contract review, lower error rates in administrative tasks — demonstrate value in business terms that procurement and compliance teams recognise.

What vendors must provide if partners are to invest

Vendors cannot expect partners to absorb pace and complexity without support. Jackson calls for transparent product roadmaps, effective technical training and explicit answers about how customer data is handled. That includes where processing occurs, what protections exist, configurable controls and how the product aligns with regulatory obligations.

Honesty about limitations is equally important. Confidence in a partner ecosystem grows when vendors disclose where a feature is unsuitable or where additional governance is required. That candour lets partners prioritise investment in the areas where they can safely and profitably advise customers.

When vendors combine clear documentation with training and practical use cases, partners can build reliable, governed services rather than one-off deployments. Jackson frames this as the route to a channel that retains customers by solving measurable problems while managing risk.

How the strategy could play out

The bottom line

The channel’s advantage is judgement, not speed. Paul Jackson’s prescription is discipline: specialise where you can deliver governance and measurable outcomes, treat AI as a matter of data flows and controls, and insist that vendors supply the documentation and training needed to support responsible adoption. Partners that follow this path are likelier to earn longer engagements and sell services that reflect operational value rather than transient feature lists.

What to watch

• Watch whether vendors publish clearer, standardised data-handling statements for AI features; no date has been set.
• Watch for partner programmes that bundle governance and adoption services as standard offers; no date has been set.
• Watch if industry-focused partner practices (vertical templates, compliance runbooks) become advertised differentiators; no date has been set.