AI or Modernization? Why SMBs Can’t Afford to Fund One and Starve the Other.
September 29, 2026
Here is a number worth sitting with: only 5 to 15 percent of organizations currently have an effective AI strategy. That figure comes from Forrester, and it lands harder when you consider how many businesses think they are already well on their way because employees are using AI tools every day.
The problem is not that businesses are using AI wrong. It is that most are using it for the wrong thing. Productivity and efficiency are valuable, but they are not strategy. And according to new Forrester research, treating them as the finish line is exactly what is keeping most organizations stuck.
Forrester’s recent Accelerate Your AI Voyage report found that 43 percent of AI decision-makers measure productivity improvements from AI, and 41 percent track efficiency gains. Only 32 percent tie AI outcomes to profit or revenue. That gap tells you something important about where most AI initiatives actually live inside a business: in individual workflows, not in company strategy.
The issue is not that productivity gains are bad. They are not. But they are also not self-funding. If AI saves your team ten hours a week, that value does not automatically translate into dollars unless something downstream changes, whether that is headcount, output volume, or how work gets priced. Most organizations are not making that downstream shift, which means the investment in AI tools is running ahead of the return.
For SMBs, the stakes are even higher. You do not have the same budget cushion that a large enterprise does for extended experimentation. If AI spend is not converting to something measurable, it tends to quietly become a line item that nobody wants to defend at budget time.
One of the sharper lines from the Forrester report: “Efficiency is not strategy; it is project management.” That reframe is worth applying directly to how most businesses approach AI right now.
Giving employees a copilot-style tool and waiting to see what they do with it is not a strategy. It is an experiment. That is fine as a starting point, but staying there indefinitely means adding AI costs without removing meaningful work from the system. Analysts describe this as “trapped work”: the tasks still exist, the human time is still consumed, and the AI tool becomes another layer rather than a replacement for something.
The organizations that are actually realizing material AI gains are the ones that started with a different question. Not “what can AI do for our team?” but “what would our workflows look like if we built them around AI from the beginning?” That is a process redesign question, and it requires someone willing to think beyond the next quarter.
For more on how SMBs can frame that question practically, AI readiness goes beyond tool selection and includes an honest look at where your current processes are and where they need to go.
There is another reason most organizations have not moved past incremental gains, and it is less talked about: most do not have the governance structures in place to support higher-stakes AI use cases.
Productivity tools are low-risk. If an AI assistant drafts an email poorly, a human catches it. But AI applied to decisions that carry real business weight, pricing, supply chain, customer risk, requires audit trails, model oversight, and accountability structures that most SMBs have not built yet. That is not a criticism. It is just where things stand.
Understanding what AI can and cannot be trusted to do without human oversight is a prerequisite for moving into higher-value use cases. The governance conversation has to happen before the deployment conversation.
Forrester outlines four areas that separate organizations with effective AI strategies from those still chasing incremental gains:
What is notable about that list is what is not on it. There is no mention of specific tools, no vendor names, no platform mandates. The strategic inputs are clarity of purpose, alignment to outcomes, and disciplined execution. The tools follow the strategy, not the other way around.
That sequence matters enormously for SMBs, who are often sold on tools before they have answered the strategic questions. A solid IT roadmap should define those questions first and work backward to the technology.
One of the more honest observations from Forrester’s research: transformational AI change rarely happens from inside IT alone. It tends to require an external forcing function, a competitive pressure, a leadership directive, or a strategic partner who can see what the organization cannot see about itself.
That is where the right MSP relationship creates real value. Not as a vendor who manages your infrastructure, but as a partner who can assess where your processes actually stand, identify where AI can be applied at the workflow level rather than the task level, and help you build toward outcomes that show up on a P&L.
The SMBs that will get the most from AI over the next few years are not necessarily the ones with the biggest budgets. They are the ones that avoid the common mistakes of digital transformation, ask the right questions early, and build AI into their operations in ways that are repeatable and measurable.
If you are not sure whether your current AI approach is a strategy or an experiment, that is worth finding out. Contact the Gibraltar team to talk through where your business stands and what a more intentional approach could look like.
