The rapid evolution of artificial intelligence (AI) has reshaped industries: driving productivity, creativity and new business opportunities. However, as AI technologies advance, businesses face the pressing need to ensure that their AI systems are deployed ethically and responsibly.

In a recent HCLTech Trends and Insights podcast, Heather Domin, Head of Responsible AI at HCLTech, shared her insights into the growing importance of responsible AI as an enabler of innovation.

The biggest misconception about responsible AI

One of the most pervasive misconceptions surrounding responsible AI is the tendency to focus primarily on long-term, large-scale risks, such as the impact on jobs and ways of working.

However, Domin highlighted that organizations often overlook more immediate and actionable measures that can mitigate risks in the short-term.

“There’s a lot that we can do right now,” she explained. “People overlook more practical actions, such as setting up the right processes, committees and groups within organizations to help manage the risks.”

Responsible AI isn’t just about addressing grand societal issues, it’s about establishing the foundational structures that allow businesses to proactively mitigate smaller risks and set the stage for long-term success.

The emergence of responsible AI as a business imperative

The findings of a recent white paper from HCLTech in partnership with MIT, Implementing responsible AI in the generative age, reveal that while 87% of executives recognize the importance of responsible AI, only 15% feel fully prepared to implement it. This gap underscores the challenge facing businesses today: while responsible AI is now a top priority, many organizations are still figuring out how to effectively integrate it into their operations.

Domin explained that while awareness of responsible AI has been growing for years, businesses are now beginning to take concrete actions.

“Leaders, even just five years ago, were aware that responsible AI was important, but today, we’re seeing much more investment and proactive steps being taken,” she said.

This shift is driven by an increased understanding that responsible AI is no longer an optional consideration, it’s a business imperative. AI’s potential for driving productivity and innovation can only be fully realized if organizations take the necessary steps to deploy it ethically.

“AI deployments don’t become successful unless you have responsible AI in place. Without it, there’s a risk of reputational damage, rework and potential fines,” warned Domin.

The HCLTech and MIT study emphasizes that responsible AI is emerging as a key area of investment for the next 12 to 18 months, reflecting the growing urgency to implement ethical AI practices within organizations.

The risks of failing to implement responsible AI

Failing to implement responsible AI can have profound consequences. A number of risks include biases in AI decision-making, security breaches and a lack of transparency.

“We've seen issues in areas like hiring or public benefits, where, without the right training data and testing techniques, people’s lives can be impacted,” said Domin.

The importance of data privacy and security related to personal information cannot be overstated, especially in the context of generative AI (GenAI). There is also a need for transparency and clear communication in AI systems.

“If we don’t have the appropriate communications, people may not understand that they’re interacting with AI and that lack of understanding can be problematic,” confirmed Domin.

Implementing testing techniques, validation processes and ensuring human oversight at critical stages of the AI lifecycle are essential to preventing these risks.

The role of regulation in responsible AI adoption

As AI technologies continue to evolve, regulatory frameworks like the EU AI Act and New York City's Automated Employment Decision Tool Law are emerging to ensure ethical deployment. While regulation is often seen as a compliance burden, Domin believes it can actually accelerate responsible AI adoption.

"When you don’t have appropriate regulations and standards, businesses often don’t know how to align,” said Domin.

Without clear guidelines, businesses struggle to define ethical boundaries, slowing down progress. For instance, measuring bias in AI systems requires clarity on protected attributes like gender or age, and laws like New York's Automated Employment Decision Law provide that clarity. “In many cases, the law now specifies how to [calculate and measure fairness and bias], which helps businesses move forward,” she added.

Regulation, when done well, provides the necessary structure to speed up responsible AI implementation. “Regulation becomes an enabler, helping organizations align with societal expectations,” said Domin, noting that many tech executives support sensible regulations that foster both innovation and ethics.

Moving forward: Responsible AI as an enabler of innovation

The future of AI is not just about managing risk but also about enabling innovation. Responsible AI can drive creativity, enhance productivity and offer organizations a competitive advantage.

“AI helps with upskilling, creativity and many things that organizations want to take advantage of because they understand it can lead to a competitive advantage,” said Domin.

The key to AI's long-term success lies in ensuring its ethical and responsible deployment. By addressing risks today, businesses can unlock the full potential of AI, creating a future where innovation and responsibility go together.