Navigating the trifecta: Growth, sustainability & compliance

In finance, it’s easy to get caught up in numbers alone, but what really drives sustainable growth is the discipline behind how we make decisions and the way we adapt to change.

Over the past few years, our business has expanded rapidly across Europe, adding channels, scaling streaming platforms, and building new partnerships, yet every move we’ve made has been anchored by a simple principle: if it isn’t profitable in year one, we don’t do it.

That mindset has shaped how we negotiate, how we innovate, and how we use technology. Automation has already transformed the way we operate, freeing people from manual processes so they can focus on analysis and strategy.

And now, with artificial intelligence racing ahead faster than regulation can keep up, finance has an even bigger role to play, not just in approving the numbers behind an idea, but in ensuring the business understands the risks, the ethics, and the opportunities of what comes next.

In this article, I want to share the lessons we’ve learned on balancing growth with financial discipline, how automation and AI are reshaping the finance function, and why upskilling our people is the key to staying relevant in an unpredictable world.

Growth in Europe: A finance-driven approach

Our European business has been almost three decades in the making.

What started in 1995 with a single TV channel in the UK has grown into a portfolio of seven channels reaching diverse audiences - from the South Asian diaspora to German, English, and Nordic viewers.

Alongside this, we’ve built our own streaming platform, ensuring we’re present across every distribution model: free-to-air, paid channels, and apps.

By the mid-2000s, we had already reached all Asian households in our footprint. Expansion from there meant rethinking our approach. The key was localization - dubbing and subtitling our content into local languages so we could reach wider mainstream audiences.

That decision has been pivotal in establishing us as the largest South Asian broadcaster and content aggregator in Europe, now reaching 40–45 million households.

From a financial perspective, our strategy has been simple but firm: no project moves forward unless it shows profitability in year one. In an industry saturated with content (Netflix, Amazon Prime, and countless others) that discipline is essential.

Our programming and marketing teams must demonstrate clear returns before any launch. That rigor has driven nearly 80% top-line growth in just the last three to four years.

Equally important has been the way we manage partnerships. With platforms like Samsung, LG, Sky, Virgin, and Vodafone, our approach has always been transparent and grounded in fair margins.

If our cost is $100, we ask for $122 (not $300) because the target is a 22% gross margin. That honesty has consistently secured favorable deals and strengthened long-term relationships.

It’s a reminder that finance isn’t just about numbers on a spreadsheet; it’s about building trust that creates value for both sides.

The impact of artificial intelligence

The last three years have seen an explosion of artificial intelligence products from the world’s largest tech companies like Google, Meta, Microsoft, and others.

Some have worked, many have not, but the sheer speed of development is overwhelming. ChatGPT was released in late 2022, and by 2024, the pace of change is still faster than most of us can realistically absorb.

From my perspective, that speed is both exciting and unsettling. The challenge isn’t whether AI will reshape our industries because it already is, but whether humans and businesses can adapt quickly enough to keep up. That uncertainty is what makes it feel, at times, a little scary.

Rather than waiting for clarity, we’ve focused on applying AI tools where they can create real impact in media and entertainment. With 150 TV channels worldwide, a streaming platform in 190 countries, and hundreds of millions of active users, the opportunities are vast. But so are the responsibilities.

Operating in regulated markets like the UK and Europe means we must ensure compliance, whether it’s avoiding inappropriate advertising before 9 p.m. or managing content standards. AI and automation play an important role in helping us meet those obligations.

Automation in broadcasting

In fact, our automation journey started long before AI became a buzzword. Between 2011 and 2014, we rebuilt our systems so that compliance checks and back-office processes could run seamlessly without manual intervention.

Today, from the moment a sales contract is signed to the point an invoice is issued, everything is automated.

I often say that AI is just automation with a new name. You tell the system what to do, and it does it. What matters is the value it creates. For us, automation has reduced errors, accelerated turnaround times, and freed finance teams to focus on analysis instead of administration.

Crucially, there were no job losses. Instead, our people upgraded and upskilled themselves to work with the new systems.

That shift has been one of our biggest successes, not only in making operations more efficient but in proving that technology and people can grow together.

Innovations in streaming services

Our streaming platform has become a testbed for applying AI in ways that directly enhance user experience.

One project we’re working on is a chatbot integrated into the app. Imagine asking, “What time is Britain’s Got Talent airing?” and getting an instant, accurate response. That’s the type of user-friendly capability we’re building.

Unlike broadcast TV, where platforms like Sky or Virgin control the interface, our streaming apps give us the freedom to innovate. And importantly, finance is deeply involved in every step of this process.

No idea moves forward just because it sounds exciting; it must be backed by clear financial projections. We ask:

How many users will engage with the feature?
What’s the revenue potential?
How can sales teams monetize it effectively?

Every innovation is vetted through this lens, ensuring that new features deliver both a better user experience and measurable business value.

Trends in AI adoption

AI adoption is advancing at different speeds across industries. Computing companies lead the way, while service industries lag behind; and the reasons are obvious.

In tech, faster development is a competitive necessity, while service businesses are still grappling with how to apply these tools effectively.

Key trends worth noting:

Rapid uptake in computing: Developers use AI to accelerate coding, with humans overseeing quality rather than writing every line themselves.
Slower progress in services: Adoption is constrained by regulatory, ethical, and practical challenges.
Massive investment ahead: AI spending is projected to hit around $100 billion globally in the next three to four years, with potential to grow even higher.
Opportunity for enablers: Service and consulting companies (especially those developing tailored AI tools) are poised to capture significant value as demand scales.

For finance leaders, the message is clear: AI investment isn’t slowing down. The real question is how to position your business to take advantage of these shifts, while balancing risk, regulation, and return on investment.

AI as automation

When I look at artificial intelligence, I see it first and foremost as automation. Invoices, reports, reconciliations - these are already being handled by systems.

AI is simply the next step in asking a system to do what we once did manually. At its core, it’s not magic; it’s automation with greater speed, scale, and adaptability.

What excites me is the potential to bring that same immediacy we experience in our personal lives into finance. When a breaking news alert flashes on your phone, you don’t wait until the evening to catch up, you see it instantly.

Why shouldn’t business performance updates work the same way?

Imagine a notification that says, “Breaking news: sales target achieved,” or “Cash flow alert: variance detected.”

That’s what we’re building - an internal app that pushes real-time updates to decision makers. Today, it shows up in our dashboards; soon, it will live on our mobiles. For CFOs and finance teams, this could be a genuine game changer.

Center of excellence for innovation

To take this further, we created a center of excellence in Bangalore - what we like to call our “center of innovation.” Its purpose is simple: bring together data and people across all departments, not just finance, and turn complexity into clarity.

In media and entertainment, no two days are alike. A program that succeeds today may fail tomorrow, and business priorities can shift overnight.

The center of excellence helps us stay ahead of that unpredictability by building tools, processes, and modules that streamline workflows and accelerate decision making.

It’s not only delivering value to the business as a whole but also equipping finance with the agility to respond faster, with better information, in a constantly changing environment.

Challenges in content prediction

Content performance is one of the most unpredictable aspects of our business. You can spend millions on a new show or film and still have no guarantee it will resonate with audiences.

Everyone expected the latest Lord of the Rings series to be a blockbuster, yet it underperformed on Amazon Prime. On the other hand, some programs (like Game of Thrones) become cultural phenomena almost overnight.

For finance teams, this unpredictability creates real challenges. A million-dollar episode that attracts only 10,000 viewers and half a million in revenue is a loss we must absorb.

To manage this, we’ve built systems that continuously gather and analyze performance data, feeding it back into our planning and forecasting.

It doesn’t eliminate the uncertainty, but it helps us quantify risk and make faster, better-informed decisions.

Sales process improvements

On the sales side, we’re working to remove inefficiencies that slow down negotiations.

In the past, a salesperson might be in the middle of a multimillion-dollar deal but still need to call a manager for discount approvals. With hundreds of clients, this created delays and uncertainty.

We’re now developing AI-driven modules that benchmark deals and enable instant decision-making in the field. The idea is simple:

Salespeople get automated guidance on what level of discount is acceptable.
Approvals happen in real time, with notifications sent to managers and finance teams.
The system tracks balances and revenue targets so we know immediately what needs to be covered elsewhere.

This approach saves time for both our teams and our clients. Deals can be closed face-to-face without delays, reinforcing trust and demonstrating professionalism.

While the system is still under development, I’m convinced this is the future of sales - a combination of human relationships supported by real-time data and finance oversight.

Global AI leadership perspectives

Looking at AI adoption globally, my personal view is that China will lead in implementation, followed closely by the United States. The sheer scale of companies, people, and processes in China gives them an advantage in speed and scale.

India, meanwhile, will play a pivotal role as the engine room for software development and system integration.

Companies like TCS and Infosys are already supporting global industries, from healthcare to media, and their expertise will ensure India remains central to building digital and AI-driven solutions for businesses worldwide.

Waiting for accounting standards to catch up

One of the most interesting questions around AI isn’t technological, it’s regulatory.

In finance, we can only move as fast as accounting standards allow. Whether it’s IFRS or GAAP, regulators will need time to decide how AI-driven processes should be treated.

And because those standards apply across industries, from media to manufacturing, the response will take a broad, macro view.

The question isn’t whether AI can consolidate accounts or generate regulatory reports, it already can. The real question is whether regulators will accept filings created by AI systems without human intervention.

Should there always be a human in the loop?

How will internal controls, ethics, and accountability be defined in an AI-driven environment?

These are the areas where clarity is still missing. For now, we continue to rely on in-house systems to consolidate and report, even though AI could technically handle the entire process.

We simply don’t have the regulatory green light. And until that comes, businesses everywhere will face the same wait.

Strategically, partnerships like Nvidia’s with Reliance Media highlight how fast AI ecosystems are developing in India and globally.

India, with its strength in software and systems implementation, will undoubtedly play a central role in shaping how these capabilities are built and deployed.

But when it comes to financial reporting, no amount of innovation can bypass the need for clear, consistent, and fair standards that apply equally across industries.

Ethics in AI regulation

When regulators and accounting bodies eventually move to formalize the use of AI in finance, they won’t do it lightly. Any AI-based system or requirement will need to be thoroughly tested before a green light is given.

The tools already exist and companies are using them every day, but from an accounting standards perspective, the framework isn’t there yet.

The challenge lies in defining how AI-driven processes fit within established principles of control, accuracy, and accountability.

Some of the key questions regulators will have to address include:

Human oversight: Will filings produced by AI require a human sign-off, or can they stand alone?
Internal controls: How do we ensure checks and balances remain effective when entries are automated?
Consistency: Should automated transactions be treated the same way as AI-generated ones?
Configuration risks: If errors arise from system settings, who is accountable - the software, the business, or the individual?

These are not trivial issues. For example, we already consolidate accounts through our in-house systems. Tomorrow, that same process could be managed by AI, but whether regulators will accept it without human intervention remains uncertain.

Ultimately, AI doesn’t remove the need for governance; it just shifts the focus to new areas of risk and responsibility. For finance leaders, the ethical dimension (ensuring fairness, transparency, and accountability) will be just as important as the technical capability.

Understanding AI hype in finance

There’s a lot of noise around artificial intelligence, but in many ways, it has been with us for years. Systems like SAP already generate reports, forecasts, and cash flows - functions that are, by definition, forms of AI.

The question is not whether AI exists in finance, but which parts of it are genuinely transformative and which are simply hype.

For finance leaders, the key questions are: is AI actually driving the business, and is it adding measurable value? If not, it may be a distraction rather than a solution. The same applies when evaluating new tools.

Legacy systems like SAP are proven and secure, while many newer SME platforms are agile and innovative but raise questions around data protection and long-term reliability.

These uncertainties must be weighed carefully before adopting any AI-driven solution.

The need for upskilling in finance

Regardless of how the technology evolves, one thing is certain: finance teams cannot stand still.

As automation takes over more transactional processes, the role of finance professionals will shift. Clerks and managers who once focused on ledgers and entries will need to move up the value chain.

That means stronger analytical skills, greater business orientation, and the confidence to ask commercial questions, not just process invoices. Upskilling is no longer optional, it’s the only way to stay relevant.

As leaders, we have a responsibility to support that journey, ensuring our people grow alongside the systems rather than being displaced by them.

Beyond automation: Skills for a complex world

AI-driven software can project cash flows and estimate sales, but it cannot account for geopolitical shocks. Elections, wars, or sanctions can reshape forecasts overnight.

We experienced this firsthand in Russia, where we reached 22 million households, only to shut down operations entirely when sanctions took effect. No algorithm could have predicted that.

This is why finance professionals must go beyond processing numbers. They need to understand global events, recognize the business risks they create, and factor those into forecasts. There is no room for complacency.

At the same time, automation has already eliminated much of the traditional accounting workload. We haven’t hired clerks for years because invoicing and ledgers are fully automated.

Instead, we’ve focused on upskilling our teams so they can contribute where it matters: cash flow forecasting, customer service, and commercial insight.

When a partner like Sky makes a payment, the job isn’t just to record it, it’s to ask the next question: What opportunities lie ahead? Are there new products or collaborations we should prepare for?

That mindset shift is what keeps finance relevant in a world where systems handle the transactions, but people still drive the business forward.

Enhancing business knowledge in finance

For me, the true value of finance professionals lies in how much they contribute to the business itself.

The moment a finance person brings revenue into the company by strengthening customer relationships, identifying opportunities, or supporting new products, their value increases exponentially.

It’s not just about protecting the bottom line anymore; it’s about helping to grow the top line as well.

Upskilling is essential. People want to earn more, and in today’s economy, the only way forward is to expand their capabilities. Finance teams must understand not just ledgers and compliance but also the commercial levers of the business. That’s how they remain indispensable.

The future of finance careers

We’ve been open and honest with our teams: automation is here to stay. But rather than reducing opportunities, it shifts them. Those who stay static risk becoming irrelevant in a year or two. Those who adapt will thrive.

Our own European operations are proof. In the early 2000s, we had around 150 people. Today, we run the same business with just six, yet our profitability is at the same level as when we had a monopoly in the market.

The difference lies in how we embraced automation, streamlined operations, and redeployed talent into higher-value work.