How to get the best from AI without losing humanity

Guest post by David Stokes, an advisor at Quant, a pioneer in Agentic AI, 

AI Adoption Is Not a Technology Decision

For all the noise – and headline-grabbing numbers – surrounding Artificial Intelligence, one reality remains consistent across every serious boardroom conversation: some roles will not survive this transition. The World Economic Forum has quantified that reality – 92 million existing positions globally are projected to be eliminated by AI before 2030. In an Irish context, where research indicates that 63% of roles carry meaningful exposure to automation, this is not an abstract global statistic. It lands close to home.

For those entering the workforce, building careers, or planning the final chapter of a professional life, that figure demands honest engagement. The question is not whether disruption is coming. It is whether leaders and organisations are positioning themselves to be on the right side of it.

The Number That Changes Everything

The headline figure rarely travels with its companion statistic. That same WEF report projects the creation of 170 million new roles as a direct consequence of AI adoption. The net result is 78 million additional professional positions worldwide – growth, not contraction. In Ireland, AI deployment is forecast to contribute in excess of €250 billion to GDP by 2035. The trajectory of investment is not decelerating. Organisations that treat this moment as a threat to be managed will find themselves overtaken by those treating it as a capability to be built.

The more precise framing is this: the future of professional work is not human or AI. It is human and AI. For most organisations, that distinction will define competitive performance over the next decade. But whether Irish organisations capture that opportunity will depend far less on which tools they deploy than on how their leaders choose to lead through the transition.

The Human–AI Collaboration Imperative

Early empirical evidence is striking. Studies indicate that professionals augmenting their work with AI tools see productivity gains in the region of 40%, with a concurrent 18% improvement in accuracy. These are not incremental improvements – they represent a structural shift in what individuals and teams are capable of delivering. When AI absorbs the repetitive, rules-based work, human capacity is redirected toward strategic judgement, relationship complexity, and creative problem-solving: precisely the capabilities that drive differentiated outcomes.

The organisations that will define their sectors in the years ahead will be those that architect genuinely integrated human–AI operating models where agents and professionals function as a coherent unit, each amplifying the effectiveness of the other. This is not a futurist proposition. It is an operational decision that leaders are making now.

What Leadership Looks Like in This Environment

The first mark of any leader navigating an AI transition is credibility through practice. If you are mandating adoption, it helps to be a visible and genuine user of the technology yourself. There is no more powerful signal to a team than watching their leader engage with AI tools substantively – learning publicly, adjusting, improving. It shifts the cultural frame from imposition to shared endeavour.

The second priority is sustained investment in people. Individuals who feel that AI is being done to them, rather than enabled for them, will disengage. Structured upskilling programmes, designed not merely to train tool usage but to help people understand how their roles evolve and where their value compounds, become the foundation of a sustainable transition.

Third, identify and amplify your early adopters. Celebrate those achieving measurable results through AI integration. The effect operates on two levels simultaneously — it reassures those who are uncertain, and it creates a performance culture where the competitive instinct works in the organisation’s favour. The compounding effect on overall capability is significant.

Transparency as a Leadership Differentiator

There is a particular cohort entering the workforce today for whom AI is simply a baseline expectation. They would be more surprised by its absence than its presence. Recruiting for AI proficiency, building it into the hiring process, and treating it as a core competency alongside any other technical or professional skill reflects where the market already is.

The colleagues already inside your organisation benefit from something different — and arguably more important: genuine transparency. What AI is being deployed, for what purpose, what governance frameworks are in place, how bias is being identified and mitigated, and how their data and your clients’ data are being protected. The seriousness of this obligation is not lost on regulators: the Central Bank of Ireland dedicated an entire spotlight section of its 2025 Regulatory and Supervisory Outlook to AI in financial services, specifically examining its deployment across trading, fraud detection, credit scoring, and underwriting. The message from Ireland’s financial regulator is clear – AI governance is already a live supervisory priority. Town halls, team conversations, and direct dialogue are not communications exercises. They are ‘trust architecture’.

A Perspective the Data Consistently Supports

Leaders who have navigated multiple decades in professional life have already lived through several supposedly existential technological disruptions – the internet, SaaS platforms, cloud infrastructure, mobile. Each was predicted to fundamentally destabilise employment. Each instead expanded it. AI will follow the same pattern, but the magnitude of its transformative potential is categorically greater.

The leaders and organisations that will capture that potential are those who refuse to treat this as a binary choice between the human and the artificial. The opportunity -and the responsibility – is to architect something more powerful than either alone.

David Stokes is a former Senior Executive, EMEA and Chief Executive, UK at IBM. He’s now Strategic Advisor at Quant, a pioneer in Agentic AI, which develops cutting-edge digital employee technology.

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