How to introduce AI in the workplace successfully

How can employers introduce AI tools responsibly?

Defining how AI will be used across roles and workflows
Providing structured AI training and capability development
Establishing governance, privacy and quality controls

AI is becoming an increasingly sizeable presence in the workplace, with 60% of employees using it on a day-to-day basis. But if you look beyond that headline number, a more complicated picture emerges – with only 22% of employees reporting that their employers had provided direct training or support in its use, the reality is that a lot of people are left flying blind or taking it upon themselves to catch up.

Adoption is moving rapidly, but it’s important to remember that enablement and capability are the more significant success markers when it comes to AI in the workplace – it’s not necessary to be the first to the table; but it’s important to be ready to eat.

The Hays Salary Guide FY26/27 highlights this as a growing divide between fast-paced AI adoption and responsible, skill-based integration. The businesses who are pulling ahead are the ones who have taken steps to close or avoid that gap, building capability and confidence in their teams before throwing them in the deep end. With businesses increasingly under pressure to adapt quickly, the question remains: how do they ensure a smooth roll-out and avoid the AI knowledge gap?

According to the Hays Salary Guide FY26/27:

60% of employees already use AI at work
Only 22% have received employer-provided training
69% of hiring managers assess AI capability through practical examples
- 52% use internal assessments
- 49% rely on references

What are the 3 key steps to responsible AI adoption at work?

1. How can businesses integrate AI into existing roles and workflows?

One of the biggest fears that employees have with AI is that their jobs and responsibilities will be eclipsed, so it’s important to be upfront with your teams about how it will be incorporated into existing workflows. Visibility and transparency are key – not just for your employees, but for your clients as well.

Start by identifying repetitive or time-consuming parts of your team’s output and testing whether an AI may be able to help streamline those tasks. Focus on productivity, with a view to opening up time for your employees to thrive in the more hands-on aspects of their work, but remember that it’s not a case of one-size-fits-all so trial and error may be a worthwhile method in establishing a new way of working.

2. How do businesses train employees to use AI?

The teams who are succeeding are those with the support and knowledge to apply AI tools strategically, so training is the first step. This upskilling needs to be enacted holistically and with clear structure, but when starting from scratch it’s fair to say that this comes with its own share of hurdles to overcome.

It’s crucial that businesses establish an understanding of their teams’ base level competencies so they can scale and train effectively across the board, but without an accepted professional standard for demonstrating AI competency in the job market, many employers are struggling to accurately gauge where their employees sit on the capability scale.

When asked how they assess AI capability in hiring, 69% of decision-makers looked for portfolio or practical examples, 52% use internal assessments or practical tests, and 49% rely on professional references. This ambiguity can be frustrating, but it also signals a clear opportunity for businesses to proactively develop protocols, training methodologies, and standards that work for them.

It’s also important to recognise that support and development need to be ongoing, with regular check-ins to ensure that all team members are across any new updates. Encouraging the development of soft skills like adaptability and agility can make a huge difference, as these skills provide employees with a firm learning foundation in the face of rapidly shifting technologies.

3. What are the risks of AI adoption in the workplace?

The integration of AI holds a lot of promises – productivity gains, streamlined workflows and rapid development, to name a few – but before it can deliver, organisations need to do due diligence and build some basic structure into how it’s used.

Guard rails don’t need to be complex to be effective – it can be as simple as defining approved tools, setting clear expectations around data privacy and confidentiality, and establishing comprehensive quality checks so that AI-generated output is reviewed before it reaches clients, stakeholders or consumers.

Without that structure, businesses could expose themselves to data errors and inefficiencies at best, and public-facing reputational risk at worst – so it’s vital that these considerations are made at the onset of your AI adoption, not as an afterthought.

The bottom line

In 2026, AI adoption doesn’t start and finish at installation. It’s a process that needs consideration, intentionality, and ongoing support to demonstrate results. Simply being aware of AI is no longer enough to create an advantage for your business. The onus is on both employers and employees alike to move forward with an open mind, an eagerness to learn, and a robust foundation for learning and support.

For more insight into how AI adoption is affecting workplaces in Australia and New Zealand, download the Hays Salary Guide FY26/27.