AI adoption outpaces enterprise capability
Enterprises risk $10.9m annual losses as AI investment accelerates but digital adoption lags, with workers losing hundreds of hours to poorly integrated systems.
Enterprises are investing heavily in AI but failing to realise value, as weak digital adoption limits impact at scale.
A study commissioned by Whatfix and conducted by Forrester Consulting estimates that a mid-sized organisation of around 1,000 employees could lose $10.9 million annually due to poor digital adoption.
The report shows a widening gap between technology investment and workforce capability. 76% of senior leaders say AI adoption is a priority, yet only 27% view digital adoption as a critical enabler.
This misalignment is reflected in day-to-day productivity. Employees are estimated to lose 728 hours each navigating complex or poorly adopted systems, highlighting persistent friction in enterprise environments.
The survey was with 335 senior decision-makers in North America, Europe, APAC and India, and mostly at enterprises with annual revenues above $1 billion.
More mature approaches to digital adoption are linked to stronger outcomes. Organisations with higher levels of adoption maturity report better user experience and greater ability to realise returns on technology investments compared with less mature peers.
The findings add to a growing body of evidence that AI performance is hampered by readiness. Business, broadly, is not prepared or able to unlock the potential value from AI and advancing technology and is hampered by how effectively new tools are embedded into workflows.
Further coverage this year consistently highlights similar constraints: organisations are losing a significant share of AI-driven productivity gains, often through rework, limited learning provision, slow role redesign and internal misalignment. A widening gap is emerging between AI capability and workforce readiness, with execution still constrained despite continued investment.
Get the report: Driving Digital Adoption For Impactful Transformation & Growth
Learning investment emerges as AI’s key differentiator
Nearly 40% of AI time savings are lost to rework, with organisations that invest in skills and learning far more likely to realise real value.
AI value depends on learning speed
AI tools are advancing quickly, but learning and role design now determine whether organisations realise value or simply accelerate activity.
AI's learning gap gets multi trillion dollar price tag
Economic modelling finds that AI alone will not deliver expected productivity gains, with learning and skills development identified as the key constraint on value, potentially worth up to $6.6 trillion to the US economy, over a fifth of GDP, by 2034.
Workload is the blind spot in AI-driven work
New employee experience research shows 36% of employees do not feel able to cope with their workload, pointing to sustained pressure at work.
Learning becomes the constraint on AI productivity
AI tools scale faster than learning systems. Skills and role design lag behind adoption. Time saved lost to checking and rework. Learning now limits AI value.
Internal misalignment slows AI-era execution
New EQ data finds internal friction and misdirected development, not AI skills, are slowing execution.