AI Project Management Tools Are Everywhere. The Productivity Gains Are Not.

AI tools for project management have never been more accessible, but a major new report suggests that access alone isn't moving the needle on actual productivity. According to McKinsey's Superagency in the Workplace report, enterprise access to AI project management tools has grown 50% year over year, yet the outcomes those tools are supposed to deliver remain largely out of reach.

The Details

The most striking finding: just 1% of companies describe themselves as having achieved "mature" AI adoption with measurable productivity results. That gap between tool availability and business impact is not a minor discrepancy; it points to a systemic problem in how organizations are implementing AI.

Several patterns explain why deployment isn't translating to results:

• Teams are adopting AI tools in isolation, without integrating them into broader workflows
• Organizations lack clear metrics for measuring what productivity improvement actually looks like
• Employees are using AI features sporadically rather than embedding them into daily processes
• Leadership buy-in exists at the procurement level but not at the workflow design level

The report also notes that companies investing in change management alongside AI tools see meaningfully better outcomes than those that simply roll out software and expect results.

Why This Matters for Service Providers

For MSPs and telecom resellers, this data is a direct signal about client conversations you will be having in the next 12 months. Your clients are buying AI-adjacent tools, they are not seeing returns, and they will eventually ask you why.

The opportunity here is positioning, not product. Service providers who can help clients connect AI tools to actual business workflows, rather than just licensing and deploying software, will hold a stronger advisory role and reduce churn risk. This is especially relevant if you are already pitching or delivering AI voice solutions; the same adoption gap exists there, and clients who understand the implementation gap are easier to retain when you can help close it.

If you are thinking about how to frame this in a client conversation, the article How to Pitch AI Voice Agents to Your MSP Clients covers practical approaches to setting expectations and handling the inevitable "we already tried AI" objection.

The bottom line: AI tool sprawl without strategic implementation is becoming a credibility problem for vendors and a frustration point for buyers. Service providers who focus on outcomes over features will differentiate themselves in a crowded market.

Looking Ahead

Watch for more enterprise buyers to pull back on AI tool renewals through late 2025 as ROI scrutiny increases; that creates an opening for service providers who can demonstrate concrete, measurable value from day one.

For the full story, read the original article on UC Today.