Democratizing Access to Generative AI Tools for Everyone

The essence of any organization’s culture hinges on its approach to problem-solving. While some opt to observe and react, the frontrunners in AI innovation plunge into experimentation. As the champions of this movement, organizations that embrace a proactive stance are setting the pace in the utilization of AI and generative AI—technologies poised to redefine our work paradigms, albeit still in an exploratory phase.

As we explore further, we engage with Jaspreet Bindra, Managing Director & Founder of Tech Whisperer Limited, UK, and Dr. Shalini Lal, Founder of Unqbe. The result is a compelling dialogue filled with unique and thoughtful insights, making for a riveting discussion.

Both leaders champion the notion that today’s AI-driven culture must thrive on rapid adaptation and continuous learning to keep up with daily technological advancements. Dr. Lal stresses the importance of AI literacy, noting, “Effective AI integration extends beyond adoption; it necessitates cultivating extensive AI literacy across all organizational levels, though many still adhere to a more cautious, watchful approach.”

The transformative power of collaboration between AI specialists and business units also emerges as a central theme. This synergy is pivotal for tackling the pressing and potential future challenges that businesses face. Bindra takes this conversation a step further by outlining a visionary approach for India, drawing parallels with how UPI and UID (Aadhaar) were leveraged to revolutionize accessibility to digital services. He advocates for a similar strategy with GenAI, aiming to massively enhance productivity and digital engagement across the nation.

Moreover, the global AI landscape is marked by fierce competition and strategic positioning, with major players like Google, OpenAI-Microsoft, and contenders such as Anthropic and Meta shaping the future. This introduction sets the stage for a profound exploration of how AI is reshaping industries, enhancing productivity, and potentially redefining the competitive dynamics on a global scale.

What concrete steps can organizations take to build an “AI Culture” that fosters innovation and responsible implementation?

Shalini Lal: The first step in building an AI culture is building widespread AI literacy. This does two important things. First, it sends a wide signal about the importance of this technology in our future. Second, so much of building an AI culture is around the ‘discovery’ of AI’s potential to solve problems.

Given how widespread the applications of AI to business are likely to be, a wide-spread approach to AI literacy matters.

And this is true at the very top of the organization as well. Research shows that when an organization’s board has more people who are AI literate, the organization does better in both value discovery and implementation success. So this is an important first step.

Next, we need at least one small team of technology specialists who love using their imagination to create ‘what can be’. These are people who are quick to learn. Who are quick to build. And can infuse the rest of the organization with a sense of promise.

The world of AI is iterative. And it’s a world that is changing each day. You are looking for that special blend of action and imagination where new projects come up and are completed in weeks.

And of course, none of this is likely to happen without the organizations’ leadership believing in the importance of making an early start. You need believers at the very top.

2. How will the rise of Generative AI like GPT-4.5 and Microsoft Copilot fundamentally transform different work areas (e.g., design, coding, research)?

Jaspreet Bindra: I believe that Generative AI (GenAI) will transform most of all what we do, is how we work. It will completely change it – the same way that Microsoft Word or Excel, PowerPoint, computers, the Internet, or browsers or search changed the way we work decades back. There was a recent Microsoft Worklab Survey that said that only 40 percent of our time was spent doing creative things. 60 percent of our time was spent in communication, meetings, reformatting, presenting, etc., and this 60 percent could be either entirely taken away by Generative AI or reduced considerably because GenAI would help us do that. Microsoft CoPilot, for example, helps you gather data in your computer through prompts, create a sales pitch on Word and then you can prompt it to convert it into PowerPoint and it will do that immediately.

GitHub CoPilot does something similar for software engineers. For tens of millions of software engineers worldwide, it has considerably improved productivity by a factor of 1.5x to 2x. Going further it might go even further.

If you think about work – work is really composed of multiple tasks. Many of these tasks can be automated using GenAI, and I believe that all cognitive work like design, journalism, marketing and all creative work – whether it be visual design or writing or document editing, or summarisation of documents or creating reports or degenerating multiple copies and pitches and messages, etc. this would become faster, easier and better using GenAI. And, so, we are going to see a massive transformation of work.

This is very important because when you are doing this, what you are actually doing is increasing productivity by several percentage points and, productivity – if you go back into economic history – directly impacts prosperity. All major technologies were productivity enhancers – be it the Gutenberg Press, the Internet, Search, etc., and this productivity directly increases prosperity, leading to an increase in GDP and an increase in revenues, leading to better salaries and a better standard of living. There is a very profound effect that will happen on work through GPT4 and CoPilot.

Finally, GenAI is not just a trend or a tech it is a fundamental difference in the way humans work with their machines. And, therefore, you are talking to it in your natural language. Instead of talking to the machine in its language, the machine now needs to learn the human language – which are being rereferred to as prompts – and the way we work with machines will change considerably.

How can we make AI tools and resources more accessible to smaller businesses and individuals?

Jaspreet Bindra: Right now, it is only the beginning, so most models are in their freemium models. If you take ChatGPT, it is free. Only if you want GPT 4, you need to pay US $ 20 a month. As more and more tools come in and more open-source tools come in, the pricing is not going to be an issue – many of these tools will be free, inexpensive or almost free. Startups that will build on top of this will also find that these are very affordable or give huge RoI for small businesses, which small businesses may not mind paying. Even today, if one can afford it, spending US$20 a month on GPT4 is one of the best investments you can make as an individual and as an office worker – even if your company is not paying for it.

The problem, however, is going to be with the hundreds of millions of people who cannot afford this. And, that is where, especially in India, we will need to deliver GenAI and GenAI tools to the masses in the same way we delivered UPI and Aadhar to make Digital Public Infrastructure (DPI) a Digital Public Good (DPG). We gave that all free and we can see that our country has been digitally transformed. I believe that we should do the same with GenAI in India. I call it JanAI – Jan is a play on Gen as well as on ‘Janta’ (Hindi word for people). Basically, what I am saying is that we need to build GenAI, Large Language Model (LLM) stacks, hopefully, Indian LLMs and Bharat LLMs, as a part of the India Stack and deliver it the same way in a simple manner over smartphones – as UPI and Aadhar are delivered. This would mean that every Indian who owns a phone or a computing device – and more than a billion do – would have access to GenAI tools. We will create a country of over 100 million creators and we could use these to simplify so many things. People could use their natural language, so they don’t need to be very literate. This could have massive use cases in healthcare, education – every child could have a personal tutor. I think we need to bring that vision of DPI to GenAI. This JanAI could bridge this digital divide and make it available to smaller businesses and individuals.

Is the Chief AI Officer (CAIO) role truly essential for organizational success in the AI era, or is it just a passing trend?

Jaspreet Bindra: When the digital revolution happened, most companies realized that they needed one single individual who they could turn to for the digital transformation of the company, and so, the CDO – or the Chief Digital Officer – was born. I was the CDO at the Mahindra Group and what I realized was that more than 50 percent of the work I needed to do was cultural – how to bring about a culture change and create a digital change and a digital mindset. And, that in itself would foster digital transformation. This was not really about technology, it was more about culture, mindset, and business models. The same things are now necessary for AI. Whatever the person is called – it could be the CAIO or the CEO or the Chief Transformation Officer or the Chief Strategy Officer. Whatever it is, I think we do need a new kind of culture in organisations – an AI culture, that makes everyone become a GENAI expert,

GenAI is a democratic technology – it is not only an IT department thing, or some interns working on it, or the CEO and C-Suite getting passionate about and looking for ways to make business better. This is a technology that every single employee of a company can learn very quickly and then figure out ways in which he/ she could be more productive. And how we can look at the hundreds of tools out there that could make their jobs easier and make them more productive, leading to the better performance of a company.

To make that happen, the job of senior management is to foster an AI culture that allows this within the right guardrails and security boundaries, Making sure that every employee becomes a 10x employee by using GenAI is going to be the biggest job of the Chief AI Officer (irrespective of the designation). So, I do believe that the role of the CAIO is necessary – whoever takes the role, or if it is created, which fosters an AI culture, a culture of curiosity and experimentation and change of work and jobs.

Therefore, this role and AI culture is necessary. But the CAIO/ CDO should be collapsed into one. We already have too many like the CTO, the CIO, etc., Some people have a CISO. We don’t need so many roles. I believe that all these should be one role.

Shalini Lal: What makes AI/ Gen AI programs different from other technology implementations is that there is potential for every part of the business to be impacted. Some problems to be solved are about developing efficiency. Others are about developing higher levels of accuracy. Still others are about discovering new ways to serve your customers.

And this is true not just of one function. But of frankly, all functions. So the potential at this time is very vast. This also means that you need someone senior to help prioritize AI implementation programs.

Add to that the reality that responsible AI implementation is also about being conscious of data ethics. And conscious of the regulation that is emerging around data.

So it does seem very helpful to have a senior leader build and lead a team of AI specialists, and give direction to the organizations’ AI programs.

Yet, there is a counterview to having a CAIO that comes from the fear that the AI program might get too centralized and miss opportunities. There is merit here as well. If enough senior business leaders do not have sufficient AI literacy, they will be unable to ‘discover its potential’ to solve problems within their function.

In my view, a CAIO is helpful. Yet the responsibility for a successful AI program is a shared responsibility between the many businesses and the role. So both will be important. Having a good leader and having a shared responsibility across business.

Will the AI race truly be dominated by a Microsoft-OpenAI alliance, or can Google reclaim its lead with advancements like Gemini Ultra?

Jaspreet Bindra: I still think that the company which, despite everything, is still the clear leader is Google. Despite the missteps they made in GenAI.

AI is not only about GenAI – there is massive stuff in AI. And what Google DeepMind has done in AI with protein folding, material detection, huge amounts of enterprise AI research, with products that predict the weather, etc., is just leap years ahead of what any other company has done so far. So, I believe that Google is super-strong. I know they have made missteps in GenAI with Gemini and Bard, and those are well-known. Those, in my opinion, are teething problems and have far more to do with the culture and leadership of the company rather than the technical prowess and the inherent strengths that Google has. I believe that Google will come back very strongly.

There will be three leaders – OpenAI-Microsoft, Google and the third spot is quite wide open. Anthropic is a pretender to the throne, so is Meta, and so is Mistral. It could be any of these who take the third spot.

The Big5 of Al – I don’t see Apple and Amazon within them. Though they will use AI extensively for their products, they are not likely to be ‘AI companies’ like the others.

What are some longer-term trends and potential disruptions we can expect as AI technologies continue to evolve?

Jaspreet Bindra: There are many long-term trends and disruptions – too many to enumerate. I think the one I believe is that we will soon see the emergence of AI Agents – they will be apps that can do things with minimal human guidance. As a human creating an itinerary and trying to book flights, hotels, etc., an intelligent agent, having been fed your data, knowing your preferences and past behavior will be able to do this much faster.

Another big thing that will happen is that AI will move to the edge. A lot of AI today sits on the cloud. We have already started seeing smaller LLMs sitting on our everyday devices like phones, PCs, televisions, etc. This makes them faster, cheaper, and easier to use.

The other thing that will happen is that as programming becomes natural language-based, all of us will become programmers. There is great change coming and that is why I keep repeating that what we need in organizations to thrive on this change is an organizational culture shift, which is very necessary.

With the rise of generative AI, how can we ensure originality and creativity are not stifled in fields like design and content creation?

Shalini Lal: This is a question that so many artists around the world are very concerned with. And rightly so.

Given that AI/ Gen AI is here to stay, the question each creative person will need to ask is how they can make the best use of these tools to make what they are doing—even better.

And there are so many possibilities. Perhaps AI can help them brainstorm creative ideas better. Or, the tools can allow them to build creatives that earlier would have either been impossible or far too expensive. Or, the tools can allow them to make sure that their creative output finds the right audience.

It is a question of discovering possibilities. Just like in other fields.

Do you see a future where collaboration becomes more prominent than competition in the AI landscape?

Jaspreet Bindra: Tech companies, by their very nature, compete and collaborate at the same time. That is why the term frenemy – friend and enemy – is often used for tech companies. They cannot collaborate. If you think about it Microsoft’s Cloud has OpenAI, Mistral, Meta – I would not be surprised if it even has Gemini. Apple’s search has Google. Amazon uses Microsoft’s productivity software. There is going to be both competition and collaboration. They would be fierce competitors, but at the right places where collaboration is required, they could come together. One can already see lots of collaboration taking place – maybe not so much among Big-Tech, but between Big-Tech and the Unicorns (the big start-ups) – they work in tandem. Anthropic has both Google and Microsoft as investors, who compete against each other. Collaboration and competition – this frenemy thing – is the name of the game.