AI has evolved significantly and become embedded across multiple business operations. Research shows that professionals who use AI in their jobs save an average of 7.5 hours per week.
However, given that organisations have invested billions in artificial intelligence, only around 39% see these benefits translate into organisational earnings.
This gap shows that simply using AI tools is not enough. . To get the best return on their AI investment, organisations need a combination of technical capabilities, such as data, cloud and cybersecurity, as well as human skills such as critical thinking, communication, adaptability, and problem-solving.
Research shows that organisations investing in workforce digital transformation were 1.8 times more likely to report better financial results.
Below are skills-based approaches organisations should focus on to get the most out of their tech and their talent in an AI-driven economy.
Skills gap analysis
Organisations often invest in new technologies with ambitious expectations, only to discover that adoption is slower than anticipated. Most often, the problem is a gap between early adoption and building people’s skills.
Organisations should give employees opportunities to learn, use new skills, and adapt as technology evolves, so they achieve better adoption and long-term value.
By mapping existing skills against those required for AI-driven operations, organisations can identify gaps and prioritise areas for development.
Simon Dale, FDM Skills Lab Coach, explains: “True AI literacy is about understanding what AI can and cannot do, how to get the best from it through clear prompting, how to critically evaluate AI-generated content by spotting hallucinations and bias, and how to integrate AI into your workflow so it augments rather than replacing good thinking.”
Continuous learning and reskilling programmes are essential for workers to adapt to the shifting demands of human-AI collaboration.
Upskilling and reskilling
The skills organisations need today may look very different in two years. We already see how agentic AI has changed the way organisations operate, with 96% of technologists agreeing that agentic AI innovation will grow at lightning speed. With that, 32% of companies are currently experiencing skills gaps or expect to have them in the next few years.
FDM Consultant Victoria Bertorelli’s spent more than ten years away from consulting and questioned whether she could return. She shares, “Technology had moved on, but I realised my communication skills, analytical thinking and can-do attitude were still incredibly valuable. FDM gave me the confidence to return to consulting, and everything since has been built through continuous learning on the job.”
Now, she supports over 2,000 colleagues in the retail sector as one of two system administrators for enterprise productivity tools, working in vendor management, business analysis, security, and operations.
The key for organisations is to create ways for employees’ skills to grow with technology so that organisations can see value sooner.
As AI and automation become increasingly popular across industries, employees will be expected to adapt to these new technologies. With this, there will be a number of new job roles emerging that previously did not exist. For instance, our whitepaper, Workforce 2.0: AI Adoption and the Future of Jobs, outlined six roles set to shape the future workforce:
Prompt Engineer – Must craft effective instructions for AI systems, requiring strong communication skills, technical understanding of how AI models work, and creativity to optimise outputs across different use cases.
AI Project Manager – These professionals need project management expertise, a solid grasp of AI capabilities and limitations, and the ability to translate business requirements into AI-driven solutions.
AI and Machine Learning Engineer – These roles require deep expertise in algorithms, data structures, and model training, but increasingly also demand fluency in ethical deployment and real-world application
AI Governance and AI Ethicist – These roles require knowledge of regulatory frameworks, ethical principles, risk assessment capabilities, and the ability to balance innovation with compliance and societal impact.
Business and Data Analyst – These professionals turn data into actionable insights, requiring statistical knowledge, data visualisation skills, business acumen, and the ability to communicate findings to non-technical stakeholders.
AI Coaches and Trainers – These roles need strong teaching abilities, up-to-date AI knowledge, patience to guide learners at different levels, and the skill to translate complex concepts into practical applications.
AI and governance
Organisations need employees who understand how to work with AI responsibly, evaluate outputs critically and know when human judgement should take priority.
It’s crucial to be mindful of the potential dangers of AI technology, such as any ethical concerns it may pose, data security risks, inaccuracies, or algorithmic biases.
Organisations should also establish clear governance frameworks that define how AI is used, monitored and evaluated. This includes setting expectations around data privacy, security, transparency and accountability, ensuring AI supports business objectives without compromising customer trust or regulatory compliance.
There are many ways organisations can harness the power of AI within internal and external business processes. For instance, a leading multinational bank with over 80,000 employees and global revenues exceeding US$80 billion needed to automate its manual, human-based document review and reconciliation. Simultaneously, they had to meet strict governance standards and regulatory requirements.
In response, FDM assigned five AI-trained Python Engineers to automate manual tasks within the securitisation process, accelerate AI adoption, and drive digital transformation across the business.
Future-ready goals
Organisations should measure the impact of skills on business performance. They should analyse whether employees can adopt new technologies more quickly, move between projects more easily, and solve complex problems.
This means shifting from learning metrics to capability metrics, including asking the below questions:
- Did projects move faster?
- Were teams able to adopt new technologies more confidently?
- Did collaboration improve?
- Were employees able to solve more complex problems?
- Did innovation increase?
These measures give a clearer view of whether building skills is helping business performance and delivering a return on investment. To track progress effectively, organisations can collect data through employee surveys, performance reviews, and analysis of project outcomes linked to upskilling initiatives.
Summary
These four strategies provide a practical framework for organisations looking to strengthen workforce capability while adding business value and improving the return on technology investment.
For years, having the latest technology was the main source of competitive advantage. Now, it’s getting harder to keep that advantage. Artificial intelligence, cloud platforms, and advanced analytics are easier to access than ever.
At FDM, our consultants achieve AI fluency through intensive training covering prompt engineering, ethical AI use, and practical tool deployment, capabilities that didn’t exist in traditional education years ago.
As change speeds up, helping people grow may become one of the most valuable things an organisation can do.
Organisations that invest equally in technology and people will be better prepared to handle uncertainty, drive innovation, and build lasting competitive advantage.
What should organisations do next?
Technology alone doesn’t create value; value comes from people who can wield technology effectively. The organisations that stand out will be those that invest in human-AI collaboration skills, not just in AI technology.
At FDM, we help organisations build human–AI collaboration capability through deploying AI-enabled consultants who can integrate into your teams immediately.
Contact us to learn how our AI-ready consultants can help your organisation’s AI transformation.