Businesses now understand that they are only as good as their data. The adage, “Data is the new oil,” has sparked interesting conversations around its merit. Like oil, data must be refined first to be useful. Unlike oil, data can be reused multiple times. And while oil might soon deplete, data will only continue to grow. This is true, especially with 5.3 billion people¹ continuously contributing through every touch, tap, and swipe on their devices. Just in the last decade, our data lakes expanded from 2 zettabytes to 120 zettabytes² – a storage equivalent of 60,000 billion movies!

While we have come a long way in collecting and storing data, the real challenge is in distilling invaluable insights from this ‘Crude Data.’ These include insights into customer behavior, emerging market trends, and even predicting the future. This is no easy task, but it is a job that seems tailor-made for AI, leading us into the new ‘Data and AI economy.’

The Power And Promise Of A Data And AI Economy

Data from digital footprints holds immense value, but most of it is often monopolized or trapped in silos. For instance, sophisticated fitness apps collect and track details like our daily workouts and health metrics. Left in silos, these insights can only create so much value for the company with creative dashboards and upselling. However, this data can be more valuable to health insurance players, allowing them to assess customers’ lifestyle habits and potentially adjust premiums accordingly. These efforts clearly add immense industry value, but the story doesn’t end there.

Infosys recently facilitated an agriculture data-sharing ecosystem exemplifying the benefits of collaboration. With this platform, a farmer can move away from traditional guesswork farming to a data-driven approach with weather predictions, soil health metrics, and market trends. Farmers can also access tailored bank offers, find the best deals on supplies, and receive government grants. Every participating industry reaps benefits from this two-way shared data ecosystem.

These interconnected innovations and synergies, extending beyond industry boundaries, are undeniably establishing the groundwork for new business models, products, and services, building the Data and AI economy.

Strategies to win in the new economy

There is no quick way to succeed in the data and AI economy, but with a clear strategy and the drive to explore new ecosystems, businesses can stand out and dominate the market. Here are the key aspects that need to be addressed in the data and AI strategy.

With the right strategy in place, it is now time to discover and leverage the drivers that can enable a successful data-sharing economy. We can group the ecosystems based on the value they offer. Some help with data flow by reducing friction in the value chain, while some can be assembled around solving a business need or creating a customer experience.

Synergies in tightly coupled value chain industries

All businesses have a vast network of partners and interdependencies across the value chain. Collaborating with enterprises across the ecosystem can help achieve the collective goal. The use cases are many. Take, for instance, industries like sustainability and trans

Businesses can think outside the box and form new ecosystems that bridge industry boundaries and not just the value chain.

Synergies for hyper-personalized “Phygital” experiences

More and more consumer-focused companies empower customers to personalize products or combine services for unique experiences, acting as a central “consumer hub” onboarding other providers to ensure excellence.

Leveraging AI-powered insights into consumer preferences, the Data and AI economy delivers hyper-personalized “Phygital” experiences—seamlessly blending physical and digital interactions in a carefully curated ecosystem.

Synergies among the C-Suite and Boardroom

The most influential success factor often overlooked by companies in the Data & AI economy is top-down sponsorship within the enterprise. The CEO and the Board must be completely onboard and commit to the data and AI economy cause. They must support the organization with the right organizational structure, business, and operating model. Their ways of working should include frequent stand-ups on progress and workshops for lessons learned – centered on the data and AI economy.

Privacy cannot be the price for value

No discussion is complete in the digital era without addressing the data privacy challenge. The extensive collection and usage of personal data from smart devices raise concerns about privacy and informed consent. User consent is often buried in lengthy legal text, leading to data transactions happening without users’ knowledge. Even seemingly harmless apps, like weather forecasts, can gather sensitive information about users’ daily routines and social activities. This kind of granular data has high commercial value but rarely benefits the user. While innovative platforms offering dollars for data straight up have become popular, privacy advocates warn users against it.

Privacy considerations in data sharing are intricately complex and require careful evaluation. To ensure a bright future in the data and AI economy, companies must raise and address the right questions and enlist global support in formulating new policies.