A world of difference: AI and digital revolutionary

Interview with Rohit Adlakha; former Chief Digital and Information Officer at Wipro Limited, currently a Board Member and CXO Advisor

Rohit Adlakha was previously Chief Digital and Information Officer at Wipro and Business Head at HOLMES™ (Wipro’s Artificial Intelligence platform). With over 15 years of leadership experience, he is a Board member at School of Inspired Leadership, a vanguard of change in shaping the future of India through education. Rohit has also pioneered CXO as a Service; he is a trusted advisor to Vector Center, a company that harnesses the power of AI to deliver real-time, decision grade water intelligence where he serves as an Environmental, Social and Governance champion through technology. For Data Neuron, an Artificial Intelligence (AI) learning platform, he is focusing on Go-To-Market and business acceleration strategies. At Vaasara, the number 1 Beauty Marketplace in the UAE, he is driving growth strategies.


 

With your extensive leadership experience across international tech-led organisations, and particularly the integration of AI, can you share what you think the global adoption of AI means for business?

AI has become mainstream, with the spend going up roughly 40 per cent in the last year. Next year the spend on AI is anticipated to be about 500 billion USD.

Generative AI itself is expected to grow the global economy, currently at approximately 105 trillion USD, by about 5 trillion USD annually, but that is just one aspect of AI. For business the impact comes in three parts: economics, efficiency and experience. With economics there is the impact of AI in terms of GDP growth and organisations will consider how they can do the same work a human does at a much lower cost of operation. Efficiency comes in the form of administrative or on-boarding tasks to speed up operations, or writing and summarising text, for example. These can be reduced from hours and minutes to seconds. And, very importantly we want AI to offer a better experience to staff and customers – how can we make it quicker, less complicated and transparent.

 

“From healthcare and education, to agriculture and manufacturing, banking and retail, to leisure and customer service – the opportunities for AI to make a serious revolutionary impact are huge.”

 

There is also an argument that since the pandemic, business has become much more used to working with technology and using it to personalise our experiences. Every segment of business and wider society is getting impacted because of this. There is a much greater interaction and reliance by humans on machines and this is where AI really comes into play. There are so many different opportunities, existing and potential applications across multiple sectors and areas of society that it is driving greater diversity and inclusion. From healthcare and education, to agriculture and manufacturing, banking and retail, to leisure and customer service – the opportunities for AI to make a serious revolutionary impact are huge.

 

In your view what are the most important factors to consider to allow appropriate AI adoption at a global level?

The first big challenge is safety. Humans are happy to talk to other humans but the minute you introduce an invisible AI tool, people change how they trust and share information. We need to think about how we explain the actions that AI takes, including sources. This is going to be extremely critical.

Bias is another major area for consideration. From areas as simple as a small query through to managing cyber security for an entire organisation, it should be bias free and auditable so it can also meet many different types of regulation. It needs to be free of human bias too, so it is not contributing to the incitement of negative feelings amongst society.

Another crucial area is sustainability and the environment. For example, the amount of energy used to operate the current version of ChatGPT (4) versus the previous has increased by 35 times. AI is starting to tap into a finite set of resources for infinite potential usage. Every time you undertake a conversation on ChatGPT it uses approximately one 1 litre of water. This is for cooling data centres and goes back into the atmosphere rather than into the groundwater where we need it. Sustainable AI is going to be crucial.

There are global organisations like the World Economic Forum focused on these issues, with multiple streams where thought leaders get together and address specific topics and issues. I participated in the World Economic Forum Global Future Council on Artificial Intelligence and we published a document on AI fairness and ethics last year, so it is definitely being addressed at a global level, but we are only just scratching the surface at this point.

The major democratic elections taking place this year, and particularly in hugely populous countries like the US and India, are going to be under the spotlight for safe and reasonable use of AI. We will see what happens.

 

“We are a global economy and seemingly border-less because of our digital connectivity, but there is a corollary of that: we have become much more siloed in our approach.”

 

How might nations establish more effective collaboration for regulating AI?

Even though we are a global economy and seemingly borderless because of our digital connectivity, there is a corollary of that: we have become much more siloed in our approach. We have come together in many ways, but we have exacerbated geography, ethnicity, language, race and gender barriers in many contexts.

However global organisations, such as the United Nations, World Economic Forum, Organisation for Economic Co-operation and Development (OECD) and the G20 summit all provide the right sort of platforms. If we could give them more power and respect to set up global common standards in which every country could follow in spirit and in policy that would deliver real change.

There does need to be much more ongoing dialogue and proper discourse through direct country to country communication so we can deliver bilateral agreements, with the hope that they move to a unilateral view and position.

It is very important also to maintain the opportunity to talk and discuss regularly through multi-nation events such as tech summits and other forums. We need to be facilitating more opportunities for people to meet at a global level, express challenges and share and gain knowledge.

And finally, there must be stronger enforcement mechanisms. We need to think about how we make rules that are enforceable by law and consider ways to make companies and enterprises more accountable at a tangible level.

 

“There must be stronger enforcement mechanisms. We need to think about how we make rules that are enforceable by law and consider ways to make companies and enterprises more accountable .”

 

How crucial is the involvement of various stakeholders, including governments, industry leaders, academia, and international organisations, in fostering effective collaboration for AI regulation?

There are five main entities that I believe need to come together to make it truly collaborative. The first and foremost are governments. With over 190 countries with their own regulations, constitutions and rule of law, it is often hard to get them to collaborate with each other. However, this is going to be crucial, be it on policy, investment into innovation, large data centres or providing grants.

The second area is enterprise – large and small – where everyone plays a role and embraces the opportunity from AI innovation and demonstrates thought leadership and a willingness to connect and contribute.

Academia must play a very important part, but sometimes this can be overshadowed. There is so much intelligence, data analysis and research underway, with cross geography collaboration already in place that we must incorporate this area.

I consider data management as an entity of its own and requires a very strong exchange framework across borders where it is not infringing on data privacy or patents. A bit like the YouTube model, we need to think about how we can embed strong data sharing platforms through which offer the privacy and can manage data orchestration and the data pipeline.

The last area to consider is that of cyber risk and security to consider explainable utility and debiasing the data.

These are the five core areas that I would highlight as central to ensure successful collaborative efforts for AI adoption.

 

Can you share how you think a cohesive approach to global AI regulation might be achieved?

The fervour around AI is something I believe was similar to the gold rush of the mid-19th century. Everyone wants to be part of it and not to miss out. Whether its peer pressure or technology advancement most organisations don’t know where to start, how to do it or which areas to focus on. This means they don’t know how to drive value out of AI, and really that will only be achieved when it can complement human activity. It is becoming a widely accepted belief that humans working with AI will be much smarter than humans working against or not using AI.

So, we do need to think about how we encourage a more consultative approach. How can we ensure adoption in a safe and transparent manner? How can we enable every global citizen to contribute, whether posing a challenge or offering solution? How can we make sure that everyone feels connected?

We need a global citizenship view, how we manage society, the environment and our economies better and more safely. To do that we need to upskill human intelligence. We are so used to having knowledge at the end of our fingertips, but the ability to use that information as effectively and analytically has diminished and that is why we feel so threatened by AI. We need to upskill humans, create new jobs and different perspectives. We need to think seriously about human and machine collaboration, not conflict. That is the only way we will progress.


 

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