Dr. Kenneth Matos
Director, Insights Lab at HiBob
AI workforce transformation succeeds when organisations think about the entire work process and turn broad ambition into clear, fair, job-relevant skills that deliver real value.
In the workplace, artificial intelligence has gone mainstream. Now, the question for organisations isn’t: ‘Will our staff use AI?’ Instead, they should ask: ‘Will our employees be able to use AI well — with judgement, consistency and trust — to deliver real value?’
Leaders underestimate AI’s paradigm shift
Many organisations presume they will. According to research from HiBob — an HR, payroll and finance platform — 75% of 1,200 global decision-makers expect moderate AI proficiency to become standard in most non-technical roles within the next 24 months.1
However, Dr Kenneth Matos, Director, Insights Lab at HiBob, thinks this expectation is unrealistic. AI implementation is “a paradigm shift,” he argues. Yet, many companies are treating it like a software rollout. “AI can explore data across all functions, which has collapsed the artificial boundaries within organisations,” he explains. “This requires a different way of thinking. For true organisational intelligence, leaders need people who ask bigger, broader questions — not simply concentrate on their one, narrow domain.”
The AI skills that are most valued — and in demand
AI proficiencies are also important from an employee perspective because they are already influencing career trajectories. According to HiBob’s research, 67% of respondents say their organisations link AI skills to promotion criteria, while 50% connect them to performance ratings.1
The trouble is, ‘AI proficiency’ is a vague term which can mean different things to different people. Organisations should nail down a proper definition that tells employees which observable, job-relevant AIskillsandbehaviours will progress their careers. It will also help managers with employee evaluations and ensure that team members are fairly promoted, trained and given new opportunities when they arise. When everyone is on the same page, it turns ‘AI access’ into ‘AI capability.’
Map out how things get done in your company.
This makes it easier to determine where AI will deliver value and where it could create problems
Underlining the skills that matter most, Dr Matos explains: “Companies are looking for employees who can clearly and proactively review output, document workflows and handle sensitive data. The focus is very much on data literacy, rigour and quality.”
Creating a catalogue of capabilities to make hiring easier
Training appears to be fragmented, however. While 73% of respondents say their organisation invests in AI upskilling, no individual training topic was offered by more than 27% of organisations.1 The solution is to properly integrate AI capabilities into job roles, learning opportunities, recruitment criteria and performance reviews, rather than treating them as add-ons. “Also, because the technology is changing so rapidly, organisations need to lean into continuous learning orientation,” emphasises Dr Matos.
For companies just starting this journey, Dr Matos advises: “Map out how things get done in your company. This makes it easier to determine where AI will deliver value and where it could create problems. Then look at your skills framework. Ask yourself: ‘What skills do we want our people to be good at, and what are we asking them to do?’” Having a clear catalogue of valued capabilities creates consistent criteria for evaluating candidates in hiring and performance processes and helps identify scarce ‘hard to hire’ skills. HiBob’s research offers a starting AI skills framework and assessment tool to help organisations get started.2
Managers must coach AI transformation
Moreover, direct managers and team leaders — the people most often expected to build AI capability across teams — must be given the language, tools and time to coach a workforce through this momentous change. “The key is for managers to move into true coaching,” says Dr Matos. It’s about working through novel problems together and guiding them through the social infrastructure and politics of an organisation.”
Ultimately, companies must be ready to embrace AI transformation. “This isn’t about ‘submitting’ to AI,” insists Dr Matos. “It’s about getting into the driver’s seat and taking control.”
[1] HiBob, 2026. 2026 report: AI maturity benchmarks and where the workforce stands. hibob.com/research/ai-skills-2026-report/
[2] Sachs, T. The HiBob AI Skills Assessment tool and Skills Framework. hibob.com/hr-tools/ai-skills-assessment-tool/
