Generative AI may have captured headlines, but enterprises are increasingly looking beyond content generation towards technologies that improve business outcomes. In an interview with Tech Achieve Media, Tejas Rathod, Founder and CTO at Mobavenue AI Tech Limited, said that he believes Decision Intelligence represents the next phase of AI adoption by helping organisations make faster, data-driven decisions across marketing and customer acquisition. He also discusses the evolution of enterprise AI, shares real-world examples of AI-led campaign optimisation, and outlines what Indian businesses need to do to unlock measurable value from artificial intelligence.
TAM: Everyone is talking about ChatGPT and AI tools that can write essays or make videos. But the real future is Decision Intelligence. In simple terms, what is the difference, and why should businesses care?
Tejas Rathod: Generative AI has brought artificial intelligence into everyday business conversations by making it easier to create content, write code, or generate images and videos. While these capabilities improve productivity, they do not necessarily help businesses make better decisions. That is where Decision Intelligence comes in.
It focuses on helping organisations decide what to do next. It combines data, AI and business objectives to recommend the best course of action at every stage of the decision-making process. In advertising, this could mean identifying where budgets should be invested, which audience segments deserve greater attention, or how campaigns should adapt as consumer behaviour changes.
As consumer journeys become more fragmented and marketing grows increasingly complex, businesses need more than automation. They need intelligence that helps them respond quickly, allocate resources more effectively, and improve marketing outcomes. The next phase of AI adoption will not be defined by how much content brands can create, but by how effectively they can turn intelligence into better business decisions that drive sustainable growth.
TAM: They say data is the new oil, but many Indian companies are drowning in data without knowing what to do with it. How does Decision Intelligence turn this raw data into actual business moves?
Tejas Rathod: Most businesses today have access to more data than ever before. The real challenge is no longer collecting information but understanding what action should be taken from it. Data can tell businesses what has happened, but Decision Intelligence helps determine what should happen next. It continuously evaluates data against business goals and recommends the next best action while campaigns or business activities are still in progress. Instead of relying on historical reports, businesses can respond to changing market conditions as they happen. This helps optimise investments, reduce inefficiencies and improve overall marketing effectiveness.
For example, consider a BFSI company running a credit card acquisition campaign. During the campaign, one customer segment may suddenly become much more expensive to acquire. Rather than waiting for an end-of-week review, Decision Intelligence can recommend reallocating budgets towards higher-performing audience segments, allowing the business to improve acquisition efficiency while staying aligned with its growth objectives.
TAM: How is Mobavenue AI practicing this? Can you share a quick, real-world example of how your platform helped a brand make a critical decision that saved time or money?
Tejas Rathod: At Mobavenue AI, we believe the real value of artificial intelligence lies in helping marketers make better decisions, faster. Our platform applies Decision Intelligence throughout the advertising lifecycle, continuously evaluating campaign performance against business objectives and recommending the next best actions while campaigns are still live. Powered by our proprietary AI engine, these decisions are made in under 15 milliseconds, enabling marketers to move from manual reporting to real time optimisation.
A good example is our work with a leading online travel platform. Travel is a category where every marketing decision directly impacts customer acquisition costs. Using our AI powered decisioning engine, we continuously analysed campaign performance and optimised audience selection throughout the campaign. This helped improve click to install efficiency by 2 times, enabling the brand to acquire users more efficiently while significantly reducing the time spent on manual campaign optimisation.
We have seen similar outcomes across other industries as well. For a hyperlocal home services platform, our AI driven acquisition engine helped scale app installs by 5 times by optimising towards downstream purchase signals instead of simply maximising installs, which is exactly how we define outcome-led growth. Our objective is not to automate every decision, but to equip marketers with timely intelligence so they can focus on strategy and long-term business growth.
TAM: Looking at the Indian AI ecosystem, what is the biggest roadblock preventing companies from moving toward Decision Intelligence? Is it the mindset, the cost, or the lack of talent?
Tejas Rathod: India has a strong foundation for AI adoption. The country has a growing pool of skilled talent, expanding digital infrastructure and businesses that are increasingly open to experimenting with new technologies. The bigger challenge today is not technology or cost but organisational readiness. Many companies continue to view AI as a productivity tool for writing emails, summarising documents or automating routine tasks. While these use cases are valuable, they represent only a small part of AI’s potential. The next phase of AI adoption will come when organisations begin integrating AI into everyday business decisions. This means using AI to determine where marketing budgets should be invested, how campaigns should adapt in changing market conditions, or which customer segments offer the greatest opportunity for growth. These decisions have a direct impact on business outcomes and competitive advantage.
Decision Intelligence requires businesses to embed AI into their operating models rather than treating it as a standalone tool. Organisations that make this shift will be better equipped to respond faster, allocate resources more effectively and create sustainable business value through smarter decision-making.
TAM: If there is one piece of advice you want to give to young Indian entrepreneurs looking to integrate AI into their business today, what would that be?
Tejas Rathod: My advice would be to begin with the business challenge, not the technology. AI is generating a lot of excitement today, but its true value lies in solving real customer and business problems, not in adopting it simply because it is available. Entrepreneurs should identify areas where better decisions can create measurable business value. Whether it is acquiring the right customers, improving retention, optimising marketing investments or enhancing operational efficiency, AI should become part of everyday decision-making rather than being used for isolated tasks.
Success should also be measured by business outcomes, not by the number of AI tools an organisation has adopted. The real measure of progress is whether AI helps improve efficiency, strengthens customer experiences and contributes to long-term business growth. Finally, build systems that continue to learn and evolve. Markets change, customer expectations shift and business priorities constantly adapt. AI should enable organisations to respond to these changes by learning from new information and supporting better decisions over time. Businesses that stay focused on outcomes, while using AI as an enabler, will be best placed to build a lasting competitive advantage.
