Adopting AI responsibly: A People-First approach

Why responsible AI starts with people

Tech leaders recognise that artificial intelligence is about augmenting, rather than replacing, employees. To empower staff, however, organisations must balance the responsible deployment of these technologies with a robust focus on governance, team upskilling and targeted use cases.

In this article, we explore insights from a recent People First AI Advisory Board, hosted by HotTopics in partnership with Freshworks. Global executives from across industries shared their real-world experiences—what’s working, what’s not, and what responsible AI adoption really looks like today. From internal grassroots initiatives to the challenges of AI governance, here’s what leaders are learning as they put people at the centre of workplace transformation.

Adopting AI responsibly: A People-First approach

• Philosophy for work augmentation
• AI adoption
• The challenge of AI governance
• Balancing innovation with AI risks
• Human-AI collaboration for work augmentation
• Key AI challenges, considerations and recommendations
• The future of People-First AI and AI ROI
• Join the People-First AI community

People-First AI: A philosophy for work augmentation

The conversation revealed that technology executives are positive, if somewhat pragmatic, about the state of AI adoption. Leaders here described their AI journeys as everything between ‘non-existent’ and ‘early explorer’ to ‘immature’ and ‘young adult’ - but amongst all of this there was a recognition that AI’s usage should be about empowering staff to become more productive.

For Mika Yamamoto, the Chief Customer and Marketing Officer at Freshworks, the ITSM provider’s approach to AI adoption has been rooted in "people first AI" – a philosophy which views artificial intelligence as a tool to enhance human capabilities - improving productivity, performance, learning and decision-making - rather than replacing them.

“Our definition of people-first AI is that we're seeing more upskilling of individuals, because AI can take care of some of the more mundane tasks,” said Yamamoto.

The benefits of this approach are starting to emerge in how organisations are using AI. 

In a global workplace survey by Freshworks, which covered over 4,000 employees across the U.S., U.K., ​Germany, France, Australia, New Zealand, and India, workers reported that AI is helping them to eliminate busywork and to become more productive. 

Nearly every employee (98 percent) reported that they were already getting time back in their work day because of AI, and they were reinvesting that time in:

• Being more productive (71 percent)
• Doing more creative or complex tasks (66 percent),
• Coaching or mentoring other employees (67 percent). 

AI adoption requires cautious optimism 

The People-First AI advisory board showcased a remarkable diversity in AI adoption. From one sporting institution’s use of computer vision in analysing player performance to a non-profit’s prototype AI agent supporting customer service representatives, organisations are finding unique ways to leverage technology in driving employee efficiencies, enhanced customer experience and, ultimately, improved business performance.

In other examples, a media business was trialling an AI-powered marketing campaign platform, encompassing automated content creation and its own production studio for text, image and video content. Separately, a technology leader in a financial services organisation revealed how Microsoft’s CoPilot was helping to improve programmer productivity.

Amongst these positive stories, there was recognition of the need for internal advocates to champion adoption - with the marketing, operations and finance departments often leading the way,  as well as clear guidelines and governance. 

A leader from higher education highlighted a particularly forward-thinking approach, viewing AI as a growing social responsibility for all leaders in how they implement these technologies; in this leader’s case, it is paramount that the institution prepares its students with the skills they'll need in what’s likely to be an AI-augmented workplace. 

Freshworks’ Yamamoto also expressed a willingness to temper expectations around AI, even if these technologies are now readily available to most employees. 

“I'm responsible for sales, customer success and support at the company, so internally I'm accountable to drive AI initiatives across all of these functions, as well as how we're driving AI in the company overall,” said Yamamoto.

“We see a tonne of grassroots efforts happening within our company, from individual contributors to leaders. We're trying to harness that – with the need to make sure that we don't have 1,000 flowers blooming.”

The challenge of AI governance

Perhaps the most significant theme from this discussion was the importance of governance with AI adoption. 

One leader, working within the financial services industry, articulated the core challenge here: validating AI outcomes remains a complex task. With potential hallucinations lurking in AI-generated content, as well as the numerous examples of AI bias already reported by multiple media outlets, organisations must tread carefully. The consensus was clear; AI is a powerful tool, but it requires rigorous human oversight if the organisation is to drive value- and avoid reputational fall-out in the event AI systems malfunction.

One participant offered a provocative analogy here, comparing unchecked AI adoption to "putting a nuclear weapon” in the hands of a child. His point, however starkly delivered, was that a lack of careful AI governance and management could cause unintended consequences for leaders and their organisations.

Balancing innovation with AI risks: A governance-first approach

The People-First AI advisory board revealed a sophisticated approach to AI implementation. One speaker described a lifecycle approach to AI adoption, focusing on organisational readiness, development and assurance. The key is identifying high-impact areas where AI can truly augment human expertise, thereby adding value to their role and enabling them to deliver higher-value work.

One leader in financial services emphasised the importance of relevant, industry-specific data, arguing against the use of generic large language models (LLMs), while 31% of surveyed advisory board members reported data quality more generally as a constraint when looking to deploy AI internally.

The goal here is not to adopt AI for the sake of it, but to create targeted solutions which address clear and specific organisational needs - while minimising the risk.

Human-AI collaboration for work augmentation

A leader from the non-profit perspective noted that, despite the fear, uncertainty and doubt around AI, artificial intelligence is about human augmentation – "unlocking capacity", rather than reducing staff. 

This echoes the broader sentiment that AI is a collaborative tool which enables more productive employees in the increasingly AI-driven workplace.

Yamamoto shared concrete examples of this in action, such as the customer support organisation using AI to deflect initial customer queries by over 40%, allowing human agents to focus on more complex, nuanced interactions.

Key AI challenges, considerations and recommendations

Several critical challenges to AI adoption emerged during the course of this discussion:

• The criticality of trust and transparency in AI decisions (cited by 38% of executives here as the biggest internal challenge when adopting AI tools)
• Considering data privacy and security, particularly with general LLMs
• The need for continuous learning and adaptation
• Balancing innovation with responsible AI implementation

For organisations looking to implement AI, the leaders here suggested several key actions:

• Start with specific, high-impact use cases
• Develop cross-functional AI working groups – a ‘grassroots’ movement to drive change
• Prioritise data quality and governance
• Focus on augmenting human capabilities, not replacing them
• Maintain a flexible approach which can adapt to rapid market changes

The future of People-First AI and AI ROI

The People First AI advisory board meeting revealed a mature, nuanced approach to artificial intelligence. 

Organisations are moving - slowly but surely – beyond the initial market hype, by focusing on strategic, responsible implementation which puts human potential at the centre of technological innovation, supported by robust governance frameworks.

The next six to twelve months will likely see further developments in data governance, more structured AI decision-making and perhaps a clearer idea of return-of-investment - surprisingly, 31% of executives here said that they were not yet formally measuring AI’s value.

As leaders from these organisations demonstrate, the most successful approach to AI is one which sees technology as a collaborative tool, not a replacement for human creativity, empathy and expertise.

Read more about how Freshworks is pioneering People-First AI in the ITSM space.

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