Enterprise technology investment has never been higher. And for many organizations, the returns have never been harder to explain.
According to McKinsey's State of AI 2025, 88% of organizations now use AI in at least one business function. Yet only around one-third have begun scaling AI at the enterprise level, and just 39% report any measurable impact on earnings before interest and taxes (EBIT). The same pattern shows up across cloud, data platforms, and enterprise software: broad deployment, uneven value.
The gap between technology investment and business outcome is not primarily a technology problem. It is a workforce adoption problem. When new platforms and capabilities are deployed without sufficient attention to how people actually use them, the ROI case built at the point of investment does not materialize in practice.
Most technology programs are designed to deliver capability. They are not designed to deliver adoption. The distinction matters because capability and adoption produce different outcomes.
Capability is what a platform or tool can do. Adoption is what employees actually do with it, consistently, in ways that connect to business value. The two do not automatically follow from each other, and the distance between them is where ROI gets lost.
That distance tends to accumulate in predictable places.
Workflows that were not redesigned.
Adding new technology to existing workflows often produces incremental efficiency at best. McKinsey's research identifies workflow redesign as one of the clearest differentiators among AI high performers, with high-performing organizations significantly more likely to have rebuilt processes around new capabilities rather than layering tools on top of old ones. When workflows are not redesigned, employees find workarounds, revert to familiar patterns, or use new systems in ways that do not unlock the value the investment was built around.
Capability building that did not keep pace with deployment.
Technology rollouts frequently move faster than the organization's ability to use what has been deployed. Role-based training, hands-on enablement, and time to build genuine proficiency are often compressed or deprioritized in the push to hit deployment milestones. The result is a workforce that has access to new capabilities but lacks the fluency to use them effectively.
No clear line of sight from tool to outcome.
When employees do not understand how using a new platform connects to business outcomes they are accountable for, the motivation to adopt it competes with the demands of existing priorities. Adoption that depends entirely on compliance does not produce the depth of use that generates ROI.
McKinsey's 2025 research identifies a group of AI high performers, approximately 6% of organizations surveyed, that attribute more than 5% of EBIT to AI. What distinguishes them is not access to better technology. It is how they manage the human side of deployment.
High performers are nearly three times more likely to have senior leaders actively engaged in driving adoption, including visibly modeling the use of new tools themselves. They are more likely to have defined processes for when human validation of AI outputs is required. They track well-defined KPIs for their technology solutions. And they establish role-based capability training rather than generic onboarding.
Taken together, these practices reflect a deliberate investment in adoption infrastructure alongside the technology investment itself. The capability and the capacity to use it are built in parallel, not sequentially.
The most consistent driver of the ROI gap is treating adoption as something that happens after a system goes live rather than something designed in from the start.
When adoption is designed in from the beginning, several things change. Training and enablement are built around specific roles and workflows rather than generic feature coverage. Success metrics are defined in terms of behavior change and business outcome, not system access or training completion. Deployment timelines account for the time it takes people to build genuine proficiency, not just awareness. And feedback loops are established so that adoption barriers surface quickly and get addressed before they become embedded patterns.
This requires a different kind of collaboration between technology teams and the people responsible for enablement and change. In many organizations, those functions operate in parallel rather than together, handing off responsibility at the point of deployment rather than sharing it across the full delivery lifecycle.
Adoption gaps do not stay static. They compound. Every quarter a platform is underutilized is a quarter where the business case that justified the investment is not being realized. Licenses are paid for. Infrastructure is running. But the operational improvements, the productivity gains, the data that feeds downstream decisions, those outcomes require the workforce to actually use the system in the ways it was designed.
In environments where technology cycles are short and the next platform investment follows quickly on the last one, deferred adoption from one initiative carries into the next. Teams that never fully absorbed the previous change are asked to absorb the next one. The cumulative effect is an organization that is technically well-equipped and operationally underperforming relative to what its technology stack should be enabling.
The organizations closing the gap between technology deployment and business value are doing so by treating adoption with the same rigor they apply to technical delivery. Defined outcomes. Accountable owners. Measurement that starts at go-live and runs through the period when behavior change actually takes hold.
For technology leaders and their business counterparts, the implication is straightforward: the investment case for any major platform or capability should include an equally specific plan for how the workforce will adopt it, at what pace, measured how, and supported by what. Without that plan, the ROI case is built on an assumption that rarely holds on its own.
Technology creates the conditions for better performance. Workforce adoption is what converts those conditions into results.
TSG's integrated delivery approach spans technology implementation and the workforce enablement required to capture its value. From platform deployment to learning design, change strategy, and adoption measurement, we help organizations close the gap between what their technology can do and what their workforce actually delivers.