How IT leaders and employees stay competitive as AI reshapes work

AI strategy, not more work will determine future of jobs

The skills marketplace is shifting, presenting businesses and individuals with a choice: learning how to use AI tools and making them a part of how we work or failing to remain competitive.

In this article, I look at the role of IT leaders in building sustainable AI strategies, why doing more isn’t always better and how flexibility to change will drive job security.

A new culture of role creep and its dangers

AI is accelerating outputs across a wide range of activities. For white-collar workers who adopt available tools, the productivity gains are real and often substantial.

However, the Harvard Business Review reported that, in practice, AI tools didn’t reduce workload but “consistently intensified it”. Workers assumed greater responsibility, widened their remits, multi-tasked more and worked longer hours as a direct result of having more capability at their disposal.

What is particularly striking about HBR’s report is that people are expanding their workloads by choice: “On their own initiative, workers did more because AI made ‘doing more’ feel possible, accessible, and in many cases intrinsically rewarding.” Good habits of prioritisation are quietly declining, replaced by a desire to do everything.

There may also be a pressure element: as AI use becomes normalised, the expectations placed on employees and organisations to deliver greater volumes of higher-quality work are rising. But this trend may not be sustainable. Left unmanaged, there is a risk of employee burnout and diminished quality, rather than the sustained productivity gains that organisations are hoping to achieve.

To counter this, employers must step in by creating robust AI implementation strategies that tackle how technology is adopted in the long term.

While that’s challenging – especially defining a strategy that can withstand the pace of change – there’s a strong incentive. NTT Data reported that 84% of organisations with AI capabilities ‘fully aligned’ to strategic priorities saw a profit increase of 5% or more from AI. For organisational leaders who set their strategic direction and implement governance, there can be a goldmine of opportunity.

AI as a market-maker

Contrary to what the doomsayers may preach, my view is that AI is creating at least as many opportunities as it takes. That means there’s going to be movement in the jobs market, which can be great for macroeconomic growth and individual prosperity.

For example, a new generation of entrepreneurs is springing up, creating apps using vibe coding methods (generating code using AI, based on plain language prompts). Coding knowledge is no longer a barrier to entry. These products won’t be perfect – many will be bad – but they wouldn’t have existed at all five years ago.

As for larger organisations, new roles will gradually emerge and become more widespread, also impacting organisational structures. IT and core functions will become far more integrated, with roles responsible for creating and orchestrating teams of AI agents, designing workflows and ensuring data is of the right quality and structure.

So, yes, we are living through rapid and lasting change. That means, in some cases, short-term job losses are possible while organisations define their AI strategies, causing real pain to some families and individuals globally. It should not be dismissed but will not be permanent. Nor are most businesses making AI-driven job cuts – there are some headline grabbers, particularly tech firms (often pushing an AI-efficiency narrative), but in many cases it is compounding this fear disproportionately. As I have previously written, in today’s highly uncertain times, retaining embedded capacity is an advisable strategy.

The more pertinent question for most people is whether they will remain competitive relative to AI-capable peers. Those who flex to new ways of working will quickly find themselves in demand.

Adjusting our approach to work

Let me share a recent personal example.

I've been working on AI-generated spreadsheets, which I've noticed typically achieve about 50-70% of my equivalent manual efforts across multiple iterations, with the remainder requiring human intervention.

When I consider some of the more complex builds took several days manually, the timesaving quickly adds up. It means the economics and optics of building from scratch have changed to the point where it’s now a bad use of my time. Crucially though, my prior experience gives me an edge in writing good prompts, troubleshooting and in making the final tweaks to take me through to a refined product.

This observation taught me that remaining market relevant as a white-collar worker requires active and ongoing engagement with AI tools, not occasional curiosity. That includes regularly testing the latest iterations and providers, because the ‘best tool for the job’ is constantly changing.

Supporting the adjustment

To embed these skills from school level through to the workplace, we should be teaching prompt writing, agent building, the pros and cons of vibe-coding, and so on. Importantly, this is not about protecting legacy job specifications but rather giving people the skills to adapt to new ways of working.

The urgency is particularly acute for existing entry-level and clerical roles, where the risk of significant disruption is highest. But I don’t agree with the idea that young people will struggle to find a place in an AI-enabled world. Quite the reverse. Young people are some of the biggest adopters – they will help educate more established professionals and, through experimentation, be a critical part of driving organisations towards new ways of working.

IT Leaders need to provide direction

IT Leaders must also implement the right AI strategies, including alignment to new and existing tech-stacks, and appropriate culture to ensure responsible use. That’s a complex job, but urgency is critical.

Failure will result in employees burning out, unsafe data practices, a breakdown in the organisational structure and, ironically, an increase in unnecessary work.

Organisations at an early stage of readiness may especially benefit from working with Systems Integration Partners or Strategy Consultants with existing frameworks and an understanding of the nuances behind AI implementation at scale. It’s a young and evolving technology but the right support can make the difference between success and failure.

Change the narrative and engage

Finally, we need to stop selling the idea that AI will make us inevitably unemployed. That causes panic and denial and is simply untrue – it's through active and informed engagement with these tools that individuals and organisations will find the operating model in which humans and AI bring the best out in each other.

Max Rice helps organisations bridge the gaps between technology/AI, people and strategic goals. With experience driving value at global and regional scales in a range of industries, Max and the team at NTT Data leverage the latest tools and frameworks to turn complex technology investments into measurable outcomes.