The global race for artificial intelligence sovereignty has forced nations to treat the technology as a strict zero-sum game of computer ownership and chip hoarding. A groundbreaking report from Draup and the Ethical AI Governance Group (EAIGG) challenges this mindset by revealing that workforce readiness and international connectivity matter far more than total technological control.
To understand how countries can balance strategic partnerships with national security without stalling their own economic growth, the Inside AI Editorial Team spoke with Prakhar Neema, the Vice President of Research and Strategy at Draup.
In this exclusive interview, we explore the reality behind the deployment gap, the true value of national institutions, and the strategic roadmap for resource-scarce nations. Below is our complete, unedited conversation.
Inside AI: Before we dive into the report, could you walk us through your background, how you got into AI, and what led you to Draup?
Prakhar: I am currently the VP of Research and Strategy at Draup. I’ve been with the company for over seven years, starting as a consultant and moving to an engagement manager and associate director before my current role.
Draup’s work sits at the intersection of AI, talent intelligence, and workforce transformation, which is what drew me to the company and the work. I have my Bachelor of Engineering from Birla Institute of Technology, and prior to Draup, I held roles in data science and business operations.
Inside AI: As VP of Strategy & Research, and a contributor to this report, what's one number or finding from your own research that surprised you while putting this together?
Prakhar: A finding that stood out to me was that AI competitiveness is not determined solely by technological ownership. Much of the global conversation around AI sovereignty, up until now, focused on owning compute, controlling chips, and building domestic models. Our research showed that those are only a few pieces of the equation.
For example, France ranks highly in data in the ecosystem but falls behind in talent and human capital. The report's findings challenge the idea that AI competitiveness comes from owning as much of the AI stack as possible by showing that countries need to consider the broader AI ecosystem.
Inside AI: Anik Bose, Executive Director of EAIGG and the co-author of the report, said connectivity beats control, and that nations chasing complete independence may end up worse off, not better. Do you agree with that? And can you name a country that's currently making that mistake, focusing on independence over partnerships?
Prakhar: Yes, I would agree with Anik’s assessment that connectivity beats control. However, it’s important to note that the report doesn’t argue against national AI development. Instead, it urges countries to recognize which capabilities are most strategically important, own them, and rely on global collaboration to accelerate progress in other areas. Any country that tries to independently recreate every element of AI capability may actually end up slowing its progress in the long run.
Inside AI: Cross-border partnerships sound great until politics gets in the way. What happens to a country's AI plans when its partner turns unreliable?
Prakhar: There are always risks associated with partnerships. A shift in geopolitics, regulations, or supply chain disruptions could instantly change the dynamics of any relationship, which is why our report emphasizes strategic control and optionality.
The most vital aspects of a country’s AI ecosystem should remain under its control to protect against sudden changes that could disrupt a partnership. At the same time, countries need to prioritize optionality in their partnerships. They should not be solely dependent on one country but instead maintain a diverse set of partnerships for capabilities that require outsourcing.
Inside AI: Is the deployment gap a people problem, or is the tech just not ready yet?
Prakhar: AI is already exhibiting what it’s capable of. Now, the focus needs to be on ensuring that the talent and systems are in place to support it. The report highlights unprecedented global investment in AI infrastructure, from data center build-outs to frontier model development, yet organizations are still struggling to realize value and move pilot programs beyond experimentation, creating the deployment gap.
Inside AI: Talent and institutions are "critical AI assets" now. What happens to a country that has great talent but weak institutions?
Prakhar: Having skilled researchers, engineers, and AI practitioners is a great advantage for any country, but talent alone does not create a strong AI ecosystem. Institutions are the environment where talent can develop new technologies, commercialize research, build companies, and deploy AI. Without them, countries are left with untapped talent that never translates into broader economic growth.
I think of it like a car engine: powerful on its own, but it needs a transmission and wheels to actually move anything. Institutions are the transmission. Without them, all that talent stays potential energy that never turns into forward motion.
Closing this gap requires countries to look beyond technological development and prepare their workforce to implement and work alongside AI. The countries best positioned to do so will anticipate the skills and roles needed over the next 5-10 years and begin reskilling their workforce accordingly.
Inside AI: If a country with no money, no chips, and no big tech companies called you tomorrow, what's the one thing you'd tell them to do first?
Prakhar: The first thing I would tell them is to identify where AI can create value and ensure it’s needed. With the large-scale adoption of AI, too many organizations focus on automating everything instead of honing in on the areas that AI is best equipped to help.
Once the areas of support are identified, I would next tell them to take inventory of their national strengths. Do they have a strong talent pool? How about institutions for this talent to work within? Countries must decide what can be outsourced and who would be the best partners to do so with. From there, a country should have a strong starting point for its AI development.
Inside AI: Is the fear that AI will destroy jobs justified, or is this the same concern we heard when computers and the internet arrived? Back then, experts predicted mass job losses, but instead we got entirely new fields like digital marketing, web designing, digital graphic designing, software development, e-commerce and many more that created millions and millions of continuous jobs worldwide. Do you see AI following that same pattern, opening doors to jobs and industries we can't yet imagine? Or is this time genuinely different?
Prakhar: Previous technology shifts, including computers and the internet, have changed how people work and create new categories of jobs. AI is creating a similar shift, but the pace of the change makes workforce preparation especially important. As we established in our research, AI competitiveness is based on workforce readiness, not just the technology.
A separate report from Draup earlier this year cited a statistic projecting that AI-driven productivity gains could support net job growth of 78 million roles over the long term. It’s now the responsibility of countries and the organizations within them to understand these emerging roles and the new skills and requirements individuals will need to perform them, and to invest in appropriate reskilling efforts.
Inside AI: What's your one piece of advice for governments and AI leaders regarding AI sovereignty and ethical AI?
Prakhar: The most important advice I can offer is to think beyond building AI capabilities today and to focus on creating the conditions that ensure those capabilities remain valuable and responsible over time. AI sovereignty and ethical AI should not be viewed as separate challenges. Both depend on whether a country can build the right foundations that can adapt as technology and the country's needs evolve.
You can find Prakhar Neema on LinkedIn here.
