As we take our first steps into 2026, many enterprise leaders are focused on a familiar concern: how to keep employees' digital skills current. Strategies center on reskilling programs, digital academies, and AI literacy initiatives. These efforts are well-intentioned, but they target the wrong problem. The issue is no longer that employees lack digital skills. It is that the usable life of those skills has collapsed.
Technology is evolving faster than organizations can formalize roles, update training curricula, or redefine career paths. By the time a skill is taught, validated, and embedded, it is often already outdated. In this environment, treating digital fluency as something employees can "catch up on" is a losing strategy. Heading deeper into this year, enterprises must stop thinking about digital fluency as a destination and start treating it as a continuous operational capability.
The skill gap is widening despite investment
There is no shortage of data underscoring the urgency. McKinsey research shows that companies with leading digital and AI capabilities outperform competitors by two to six times in total shareholder returns. Yet McKinsey also reports that nearly six in 10 workers will require significant retraining before 2030, and fewer than half of job candidates possess the high-demand digital skills employers list in job postings. These gaps persist even as learning budgets expand.
The disconnect is structural. Traditional upskilling assumes relative stability, predictable tools, and slowly evolving roles. That assumption no longer holds. AI, automation, and workflow technologies are reshaping jobs continuously, often faster than organizations can document the change. No centralized training function can keep pace with that level of volatility.
Digital fluency is no longer an IT issue
Another constraint holding organizations back is the belief that digital fluency primarily belongs inside IT or data teams. That distinction has eroded. Business leaders now oversee AI-driven decision systems, automated workflows, and technology-enabled products. According to McKinsey's "We're all techies now" analysis, executives increasingly need foundational understanding of cloud architecture, data governance, cybersecurity risk, and AI trade-offs simply to perform their roles effectively.
In insurance, this shift is unavoidable. Underwriting, claims, fraud detection, regulatory reporting, and customer engagement are all shaped by technology decisions. When only technical teams understand how these systems function, the organization becomes slower, more brittle, and more exposed to operational and regulatory risk. Digital fluency must extend across underwriting, claims, compliance, operations, and leadership if insurers expect to adapt at speed.
Training cannot keep up. Adaptability can.
Faced with accelerating change, many organizations respond by expanding course catalogs, launching academies, or mandating certifications. These efforts provide value, but they do not solve the core challenge. Skills decay faster than training cycles can replenish them. What matters more is whether employees know how to adapt as tools, workflows, and assumptions change.
This is where the conversation needs to shift. Continuous learning is not about more content. It is about redesigning work so learning happens inside execution. McKinsey has found that while 80% of tech leaders view upskilling as the most effective way to close skills gaps, only 28% plan to meaningfully increase investment in the next few years, in part because traditional programs struggle to show return. Learning that sits outside real work rarely scales. Learning embedded into workflows compounds.
The insurance workforce will be judged differently
As digital skills become more transient, performance expectations must change. Employees cannot be evaluated solely on mastery of specific tools. They must be assessed on how effectively they adapt, challenge outputs, collaborate across functions, and apply technology responsibly.
For insurers, this means valuing underwriters who understand how models behave rather than simply how to operate them. It means claims professionals who can work alongside automation while exercising judgment in ambiguous cases. It means leaders who can interrogate AI-driven outcomes, governance structures, and risk exposure without relying exclusively on technical intermediaries.
The real challenge for 2026
The organizations that succeed in 2026 will not be the ones with the longest skills lists or the most certifications. They will be the ones that redesign work so adaptation is unavoidable and learning is constant. Managers will be expected to coach in real time. Workflows will be designed to expose employees to change rather than shield them from it. Technology will teach through use, not through periodic retraining.
The uncomfortable reality is this: no enterprise can train its way out of rapid technological change. Skills will continue to expire. That is not a failure of people or programs. It is a structural condition of modern work.
The real question for leaders heading into 2026 is not how to preserve digital skills, but whether their organizations are built to function when those skills inevitably expire.
