Across organisations, AI agents are beginning to take on tasks that once required significant human effort, from analysing data and preparing reports to managing workflows and supporting decision-making.
Major companies are already investing heavily in AI-powered platforms and software that use agentic capabilities to automate tasks, support decision-making and orchestrate workflows with increasing autonomy, signalling a future where human and agentic colleagues working together will become the norm.
As the technology continues to advance, the real challenge for business and leaders is not simply implementing agentic AI, but ensuring people are equipped to work effectively alongside it and with it. This means building both the skills and confidence needed to understand how these systems operate, while also establishing the governance, transparency and oversight required to trust their outputs and decisions. In many organisations, the biggest barriers to adoption are likely to be human and organisational rather than technological.
As Ankur Anand, CIO at Harvey Nash, explains:
"The CIOs who lead in 2026 will be the ones who treat AI agents as a new layer of cognitive infrastructure, where human intent guides the work and agents deliver the scale, speed, and precision to execute it."
The most successful organisations will not focus on replacing people with agents. They will focus on helping people and agents work together effectively.
This piece explores five practical ways leaders can build confidence in agentic colleagues.
1. Create a clear vision for human-agent collaboration
Many employees are unsure what agentic AI means for their role.
This uncertainty is often driven by a lack of direction from leadership. Our Tech Talent & Salary Report found that 20% of organisations do not have a clear AI strategy, while 51% of technologists say an unclear strategy is preventing them from achieving their technology goals.
Employees need clarity on how work will actually change in practice, not just in principle.
That means being explicit about:
- Which workflows will involve agents
- How humans and agents will interact day-to-day
- What “good” looks like in a hybrid model
- How roles will evolve over time, not disappear overnight
Clarity reduces speculation, and as we know, speculation drives fear, and leaders who define the operating model early create stability in how people interpret change.
2. Put governance before scale
Trust grows when people know there are safeguards in place.
Employees are far more likely to embrace AI agents when they understand how decisions are made, what data is being used, and who remains accountable for outcomes.
Strong governance accelerates adoption by giving people the confidence that agents are operating within clear boundaries, with appropriate oversight and accountability.
Governance should clearly define:
- What agents are allowed to do independently
- Where human approval is mandatory
- How decisions are logged and audited
- What data sources are approved and why
- How bias, drift, and errors are monitored over time
Without these boundaries, confidence erodes quickly. With them, organisations create the conditions for safe, scalable adoption.
3. Invest in upskilling, not just access
Providing access to AI tools is not enough.
While our Tech Talent & Salary Report found that 75% of technologists now have access to AI tools, only 37% work in organisations actively investing in AI upskilling through training, workshops, and certifications.
And only 43% are given dedicated time to experiment and learn with the tools they already have.
That gap matters because confidence in agentic AI (and new technology in general) comes from familiarity. Without time to experiment, employees cannot develop the understanding needed to use these tools effectively, identify where they can add value, or recognise their limitations.
As agentic AI becomes embedded across business functions, organisations will need to invest in upskilling beyond their technology teams to ensure employees can work confidently and responsibly alongside these systems.
Employees need time and space to:
- Experiment with agents in low-risk environments
- Understand where they perform well, and where they don’t
- Build new workflows around them
- Learn how to validate and challenge outputs
- Develop practical, job-relevant confidence
Without upskilling, agents remain separate from day-to-day work. With it, they become embedded in how work gets done.
4. Make accountability unambiguous
One of the fastest ways to undermine trust in agentic systems is to blur responsibility.
Even as agents take on more execution, humans must remain accountable for outcomes that matter.
That means being explicit about:
- Who owns the final decision
- Where human judgement is required
- How exceptions are handled
- When escalation is triggered
- What happens when agent outputs conflict with human insight
This clarity is what allows autonomy without uncertainty.
When people understand that accountability is not shifting to agents but staying with people, confidence increases significantly.
5. Show how agentic AI expands opportunity, not just efficiency
If AI is only framed as a cost or efficiency lever, people will naturally assume it is something happening to them rather than with them.
The reality is more complex, and from our data, more positive.
The market is already showing new roles emerging. LinkedIn’s AI Market Update found that Generative AI Engineer is one of the fastest-growing technology occupations, while hiring for AI engineering talent increased by more than 25% year-on-year in 2025.
At the same time, the Harvey Nash Tech Talent & Salary Report shows that 48% of technology professionals rank a deep understanding of technology as one of the most important leadership traits.
The organisations building confidence are the ones showing, in practical terms, how agentic AI:
- Removes low-value work
- Creates space for higher-impact thinking
- Enables faster learning and career mobility
- Opens up entirely new categories of roles
Confidence grows when people can see a future for themselves alongside the systems being built.
Building trust in the agentic future
The future of work is unlikely to be fully human or fully autonomous.
Instead, it will be defined by hybrid operating models where people and AI agents collaborate to achieve outcomes neither could deliver alone.
For CIOs and digital leaders, success will depend on more than deploying new technology. It will require creating trust through strategy, governance, communication, and capability building.
The winners will be those who help their people see agents not as competitors, but as colleagues.
Because confidence in agentic AI is not built by the technology itself. It is built by the leadership, clarity, and trust that surround it.
