We’ve all discussed that AI will significantly increase efficiency. However, AI has yet to reach its full impact; it also only performs specific tasks, not entire jobs. Interestingly, commercial benefits are rarely discussed. Similar to prior innovations, generative AI will take some time to deliver substantial economic value. This poses a unique time for talent management: while entry-level work is being reduced in an AI-enhanced world, entry-level talent is still incredibly important. Also, the time is now to (re)invest in our organisations and employees, so that we do not only deliver cost reductions, but also leverage the digitisation and automation benefits as AI improves to generate long term commercial growth.
‘An investment in knowledge pays the best interest’ (by Benjamin Franklin). We’re now in our sixth innovation cycle with digitisation, AI, robots, etc. Each cycle’s longevity has shortened due to both technology and the benefit of past learnings. Consumer demand, intense competition and the current economic uncertainty will push rapid AI adoption. The nature of our work and how we support customers will inevitably change. However, be it technological innovation or economics, transformation is fundamentally about people. Companies, such as Klarna and Duolingo, recently realised this as they reduced their workforce (citing AI adoption), but faced talent and performance (quality) challenges.
It’s essential for leaders to balance efficiency and cost savings with long-term talent needs. AI is estimated to automate 50-60% of typical entry-level tasks, i.e. drafting reports and summarising research and data. One option is to not fill these roles and leave middle and senior employees to review for accuracy and apply critical thinking. Entry-level roles have always been an opportunity for companies to gain new talent and employees to attain on-the-job-learning; eliminating such roles leaves an obvious talent gap and puts more onus on experienced employees to “finish the rest of the job”. We still need entry-level talent, just for different tasks - companies have an opportunity here to redefine “entry level”. Hiring for internships (i.e. longer than a summer programme), partnering with universities and other institutions to work on projects, and creating rotational development programmes can be beneficial ways to attract, retain and train new talent. This will also provide a pathway to build future leaders.
More experienced employees will find themselves in AI-augmented roles. It’s well known that AI has great potential for biases, hallucinations and misinformation and disinformation. Leveraging AI will allow employees to enhance workflows and create greater governance and controls to deliver the full value of generative AI. Training employees to assess and challenge output, while applying critical thinking, is an important part of deriving insights and making sound recommendations. Human judgment and accountability are still needed to manage risk and ensure performance (we can't automate accountability). And it goes without saying that communication skills will become more important than ever. These are all leadership capabilities for companies and employees to invest in.
While cost savings are always financially helpful to the bottom line, they don’t continue on forever. The commercial benefits of generative AI should equally be of great interest, and investors have expressed the need to leverage AI for growth in 2026, as communicated expectations. With more routine, rules-based tasks automated, all teams can increase their time delivering improved outcomes and experiences to their customers, both internal and external. That form is sent to all employees to complete, but it only gets returned accurately with significant follow-up. The originating team can now invest time to create one that receives improved responses. For external customers, AI can proactively detect when they need support - before they request it - and deliver better experiences, avoiding churn and basket abandonment in the purchase path. Algorithms for dynamic pricing can also be optimised to monitor competitive pricing, market changes and customer willingness-to-pay. An AI-augmented workforce is better equipped to respond - and also develop creative solutions - to customer needs.
Innovation will always propel us forward. Business transformation is a workforce change requiring new skills, redesigned roles and leadership involvement, not just a systems change. Companies where leadership work closely with their management and employees to set KPIs for the business in driving value from AI (both financial and talent development) will be better equipped to realise the opportunities and also navigate the uncertainties.
