AI has arrived faster than the foundations can support it
AI is now firmly embedded in almost all marketing conversations; not just across the IT channel but in every business. Vendors are building it into their platforms, partners are being encouraged to adopt it quickly, and leadership teams are rightly asking how it can improve efficiency, consistency and scale. For organisations operating in competitive, margin-sensitive markets, the promise is understandably appealing.
However, inside many channel marketing teams, the reality feels more complicated. While AI has undoubtedly increased the volume and speed of output, it has also surfaced a level of uncertainty that many teams were already carrying. More content is being produced, campaigns are moving faster, and dashboards look healthier on the surface, yet confidence in what marketing is actually achieving is often lower than before.
The issue is not that AI doesn’t work, but rather that AI has a tendency to expose what was never properly resolved.
AI doesn’t fix weak marketing, it accelerates it
In practice, AI is rarely introduced into a clean, well-defined marketing environment. It lands on top of inherited messaging, loosely defined audiences, evolving propositions and processes that have grown organically over time. In the IT channel in particular, marketing often has to juggle multiple vendor messages, overlapping propositions and long, complex buying cycles, frequently with limited resource.
When those fundamentals are unclear, AI doesn’t correct them. It scales them.
If positioning was vague, AI produces consistently vague content at speed. If target audiences were defined broadly, AI generates messaging that tries to speak to everyone and ends up resonating with no one. If the value proposition differs depending on who you ask internally, AI simply reflects that inconsistency back into the market.
In that sense, AI acts less as a solution and more as a mirror. It works with whatever clarity or confusion already exists.
Democratising AI without context creates noise, not value
One of the most common patterns I see is organisations rolling out AI tools widely across marketing, sales and even wider teams with the intention of empowering people and removing bottlenecks. The logic is sound. In reality, without shared context, it often creates more problems than it solves.
Teams are encouraged to generate social posts, blogs and emails quickly, but without a clearly articulated audience, agreed positioning or defined tone of voice. Personal experience and point of view are rarely discussed. Guidance on what good looks like is minimal. In the race to move faster, be louder and claim disruption, marketing has drifted further from what actually builds trust: clarity, credibility and a sense of real human experience.
The outcome is rarely stronger engagement. Instead, it’s volume. Large amounts of content that look active but feel interchangeable. Different people producing outputs that follow the same structures, use the same language and offer little genuine insight to the buyer. For IT decision-makers already overwhelmed by marketing noise, this kind of content is easy to ignore.
AI didn’t cause this problem. It simply exposed the lack of shared foundations underneath it.
Automation and personalisation amplify confusion if the basics are unclear
Automation is another area where AI can quickly give the impression of maturity. Workflows are built, reporting improves, and activity increases across the funnel. But if the underlying definitions are weak, automation simply moves confusion faster.
In many channel organisations, there is still a lack of agreement around what a qualified lead actually looks like, where marketing responsibility ends and sales responsibility begins, and which behaviours genuinely signal intent. AI-driven automation doesn’t resolve those questions. It scales them.
Personalisation often follows a similar path. Messages reference job titles, industries or recent activity, and internally this feels targeted. From the buyer’s perspective, however, the message often still misses the mark. It doesn’t reflect the reality of their role, the pressures they’re under, or where they are in a complex buying journey involving multiple stakeholders.
Relevance is assumed rather than earned. And without relevance, trust is hard to build.
The real gap is not tools, it’s decisions
The organisations struggling most with AI adoption are not short on technology. They are short on decisions. Decisions about who they are really for, which problems they solve best, what makes them genuinely different in a crowded market, and which opportunities they are prepared to say no to.
These are difficult conversations, particularly in the IT channel where propositions can be broad and services often evolve in response to vendor strategy or customer demand. For years, many teams have found ways to work around that ambiguity. AI removes that option. It can accelerate execution, but it cannot replace clarity of intent.
What effective AI-enabled marketing actually looks like
The strongest teams I see using AI well are not the ones moving fastest. They are the ones that are clearest. They invest time upfront in defining audiences properly, articulating positioning in plain language, and agreeing how marketing supports revenue across long, multi-stakeholder sales cycles.
They document what good looks like before automating anything. They use AI to explore ideas, stress-test messaging and improve consistency, not to replace strategic thinking. As a result, AI becomes an enabler rather than a crutch.
When those foundations are in place, AI genuinely adds value. It helps teams scale work sensibly, identify patterns in data, and operate more efficiently without losing focus or credibility.
Putting AI back in its proper place
Problems arise when AI becomes the strategy rather than supporting it. Too many plans are built around output targets alone: a certain number of blogs, a daily social cadence, a volume of emails to send. AI is expected to make this sustainable, but little attention is paid to whether the activity is actually meaningful.
In the IT channel, where trust, credibility and long-term relationships matter, activity without substance does little to move the needle.
AI is not a strategy. It is not a shortcut to differentiation. And it is not a substitute for leadership. It is a force multiplier, and the outcome depends entirely on what you feed it.
Feed it clarity, conviction and genuine customer understanding, and it can help marketing teams move faster and smarter. Feed it noise and unresolved thinking, and it will simply produce more of the same.
The uncomfortable truth is that AI hasn’t raised the bar for marketing. It has simply removed the excuses. The organisations that succeed are not the ones adopting the most tools, but the ones willing to fix the foundations first and then accelerate with intent.
Louise Mahrra
Louise Mahrra is a marketing strategist and channel expert.
She is the founder of The Marketing Human, a blog exploring how real human connection powers better marketing, especially in the IT and channel space.
