Build Employee Trust – and Enthusiasm – with Responsible AI

From Emily Teesdale, Senior Manager, KPMG and Mohammed Bari, Director, Powered HR, KPMG

AI, especially Generative AI, is only in its infancy, creating varying degrees of anticipation, uncertainty and wariness among employees. To build trust, companies will need to have honest conversations, clear policies and a dedication to training.


Blog Build Employee Trust with Responsible AI

Generative AI promises to usher in a new era of productivity – and companies that get it right could leave competitors in the dust. But what exactly does that look like? The truth is, no one really knows for sure.

This emerging technology, which uses advanced machine learning (ML) algorithms to generate entirely new content – from text and images to videos and presentations – is still finding its footing in the business world. Yet, business leaders understand the urgency of the situation: 80% of decision-makers agree that AI is required to keep their business competitive, a global Workday study found. If they wait until generative AI has gained traction to get on board, their organisation could quickly fall too far behind.

To stay ahead of the curve, companies are experimenting on many fronts. From automating complex tasks to brainstorming creative solutions, they’re looking for new ways to enhance efficiency and accelerate innovation. The opportunities are exciting – but it’s not yet clear what this technology will mean for employees.

“ChatGPT and other generative AI tools will very confidently answer your questions, but it’s based on the data they have access to. It's not always accurate.”

Emily Teesdale Senior Manager, KPMG

Overall, CIOs expect increased productivity, increased collaboration and increased revenue and profits to be the top benefits that come from integrating AI and ML within the IT function, according to a report from Workday on AI in IT. However, only one-third of employees say they have a good understanding of AI and how it can be used in the workplace, a Forrester Consulting survey found.   

Plus, there are several fundamental challenges that organisations must grapple with as they adopt generative AI. Ethical training, responsible use, robust governance and regulatory compliance are just a few of the critical factors CIOs must consider. Without the proper governance, AI can create more problems than it solves.

“ChatGPT and other generative AI tools will very confidently answer your questions, but it’s based on the data they have access to. It's not always accurate,” said Emily Teesdale, Senior Manager at KPMG. “So, a lot of companies are starting to draft policies and procedures to manage those inherent risks.”

Employees are interested in learning more. Roughly three in four say they hope their company explores more AI implementation.

How companies tap, train and fine-tune generative AI tools could also have a major impact on both customer and employee trust. IT leaders must demonstrate that AI can be rolled out responsibly – protecting privacy, preserving jobs and producing accurate content – to get people on board.  

For their part, employees are interested in learning more. Roughly three in four say they hope their company explores more AI implementation. But organisations need to strike the right balance between innovation and ethics to build enthusiasm about new ways of working. Otherwise, internal resistance to change could hinder meaningful progress.

Here are ways that CIOs can adopt and implement generative AI solutions that will both boost the bottom line and empower employees to drive responsible change.


Develop (and Communicate) a Clear AI Strategy  

Generative AI may seem to work like magic, but successful rollouts don’t happen overnight. Getting farther faster with this technology demands a clear vision of what the organisation wants to achieve – whether that’s boosting productivity, increasing customer satisfaction or improving the employee experience. From there, teams can start brainstorming different ways to meet those goals.  

However, what they can achieve depends on the quality and quantity of the data AI models have access to. While some out-of-the-box solutions come pre-trained on relevant datasets, most models must be fine-tuned with proprietary data to deliver the most meaningful results. That means CIOs must focus on connecting internal data in a responsible way.  

CIOs should also ensure the organisation’s AI strategy keeps scalability top of mind, thinking through how new solutions will integrate with existing processes. The point is to improve results while also staying nimble, adopting technology that can adapt as both the business and AI applications evolve.  

While proactive strategic planning is essential to make generative AI investments as effective as possible, that doesn’t mean CIOs need a fully baked plan to get started, said Mohammed Bari, Director, Powered HR, at KPMG.

“You can have a strategy cooking while you're analysing your use cases,” he said. “Don't wait, though. Go ahead, get started. Start thinking, start brainstorming and start experimenting.”


Dip Your Toe in with Specific Use Cases Targeting Pain Points

Your generative AI strategy tells teams where they should be headed. Specific use cases show them which path they should take – and that extra direction can make all the difference.   

“What we're seeing with AI is it's a bit more use-case-led,” said Bari “So, I've got a big problem in recruitment. I've got a big problem in redeploying talent. Well, how can AI solve that?”

Take for instance, a company that receives thousands of CVs every day. It’s impossible for an individual employee to sift through all of them – but generative AI can help bubble the best candidates to the top. By focusing on skills – what the business has, what it needs and what different applicants bring to the table – generative AI can quickly find the best fit. With an internal skills marketplace, organisations can also quickly find ideal candidates already in their ranks. 

While the details of each use case will vary, focusing on major pain points can help companies get quick wins – and help teams learn how generative AI really works. When people start to apply this technology to their daily work, they’ll identify potential uses that make their jobs easier. And as employees become personally invested in AI rollouts, larger productivity gains promise to appear.


Prioritise Ethics and Governance from the Ground Up

AI models are trained on massive datasets – but that doesn’t mean that data is always accurate. It could be biased, replicating the unconscious bias of its human trainers, or just plain wrong. Plus, there’s the risk that training data has been manipulated by malicious actors, as these types of cyberattacks are becoming more valuable and therefore common.

To get employees engaged, offer regular training on the company's ethics policy, relevant regulations and how to identify and address ethical issues.

In this environment, CIOs must develop a comprehensive risk management plan that addresses these potential threats to build and buy AI solutions that can be trusted. Establishing guidelines for responsible AI usage, data privacy and transparency shows employees that you care about ethical issues – and puts some of the power in their hands. While CIOs must lead by example, trustworthy AI takes commitment from everyone involved.

To get employees engaged, offer regular training on the company's ethics policy, relevant regulations and how to identify and address ethical issues. Encourage open communication by clearly outlining how employees can escalate concerns and establishing whistleblowing policies that protect employees from retaliation. Address bias before it becomes a problem by increasing diversity on teams developing and using new AI applications. Taking these steps early on will show employees that the company is taking its commitment to responsible AI seriously. 


Take the Human Impact into Account  

Generative AI could completely transform the business landscape – and employees aren’t quite sure what that will mean for them. For example, will productivity enhancements translate to layoffs? Or will their duties change in a way that outpaces their skills?

Only 16% of leaders believe that employee buy-in is critical for AI success.

These worries are realistic and CIOs need to take them seriously. If teams aren’t willing to find new ways to work alongside generative AI, innovation will be stymied. Yet, only 16% of leaders believe that employee buy-in is critical for AI success.

To make employees active participants in AI innovation, take the time to show them where humans add the most value. Highlight the strategic, creative and logical tasks that require a discerning human mind. Then help them explore how generative AI can elevate their own roles by automating the mundane tasks no one wants to do.  

Not everyone will be open to change, so find the people who are willing to adapt and invest in them as change management leaders. Skills are teachable, but attitude is not. In an uncertain environment, cultivating enthusiasm, curiosity and empathy will be key to future success, Bari said.

“The things that make us human – that make us good people and good colleagues – are the things that will make us stand out,” he said.



KPMG LLP, a UK limited liability partnership, operates from 20 offices across the UK with approximately 18,000 partners and staff. It operates in 143 countries and territories with more than 273,000 partners and employees working in member firms around the world. 


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