Can AI Help Your Company Innovate? It Depends on How You Use It

Introduction: Is AI the Silver Bullet for Innovation?

At some point, every company faces the hard truth: products get old, and what was once cutting-edge can quickly become obsolete. This realisation often leads to a pressing need for innovation - a way to refresh and reimagine product lines to stay competitive. But in a world where the pace of change is faster than ever, traditional innovation methods can feel sluggish and outdated.

As a visionary IT leader with over 30 years of experience in digital transformation, I' ’ve seen the potential of AI to drive innovation. Still, I' ’ve also observed that success depends heavily on how these tools are utilised. In this article, we’ll explore whether AI can genuinely help your company innovate and, if so, how you can harness its power effectively, particularly within the BFSI sector.

The Challenge of Innovation in Today’s Market

Innovation is notoriously tricky, especially in industries like banking and financial services, where the stakes are high and the market is fiercely competitive. The challenge is compounded by the fact that the quality and quantity of innovation have been declining. Scientific paper production and patenting have seen significant drops since their peaks in the mid-20th century. At the same time, the sheer volume of scientific knowledge has grown exponentially, making it increasingly difficult for companies to keep up.

These challenges can be particularly daunting for businesses in the BFSI sector, often characterised by long product development cycles and stringent regulatory environments. Leaders must navigate a complex landscape where failing to innovate quickly can lead to obsolescence.

Why Products Become Obsolete: Understanding the Paths to Irrelevance

Before we dive into how AI can help, it's crucial to understand the various ways products can become obsolete:

1. Long Development Cycles, Short Product Lifespans In the BFSI sector, products such as financial instruments, insurance plans, and banking services can take years to develop, but their relevance can diminish rapidly as new competitors emerge.
   • BFSI Example: Launching a new digital banking platform can take years of development, but competitors can quickly replicate its features once it's released, eroding the market share. For instance, when a leading bank launched its AI-driven personal finance management tool, several competitors introduced similar products within months, challenging maintaining a unique competitive edge making maintaining distinctive, unique competitive edge challenging.
   • Actionable Insight: To combat product rapid obsolescence, BFSI companies must focus on continuous innovation and leverage AI to accelerate the development and enhancement of their offerings.


2. Changing Business Contexts As markets evolve, so too must the products that serve them. A product that once fit a market well may no longer meet the needs of that market as conditions change. For example, the rise of electric vehicles has created new demands for components that were once considered standard in traditional gasoline-powered cars.
   • BFSI Example: The shift towards digital transactions and cashless payments in financial services has significantly altered customer expectations. Products designed for a primarily cash-based economy are now less relevant, and financial institutions must adapt their offerings to meet the demands of a digital-first world.
   • Actionable Insight: AI can help companies anticipate and respond to changing market conditions by analysing trends and predicting future demands, allowing them to adapt their products and services proactively adapt their products and services.


3. Explosion of Potential Combinations In industries with vast potential product variations, the challenge lies in efficiently exploring all possible combinations to find the most effective solutions. AI can be critical in navigating this complexity by predicting which combinations will likely succeed.
   • BFSI Example: A significant insurance company used AI to optimise its policy offerings by analysing vast datasets on customer behaviour, risk factors, and market trends. By simulating different policy combinations, the company could quickly identify the most effective and profitable insurance products, reducing the time to market and increasing customer satisfaction.
   • Actionable Insight: BFSI companies can leverage AI to explore various product variations and combinations, helping them innovate quickly and cost-effectively.

Can AI Help with These Problems? The Answer Is Yes, But…

While AI holds tremendous potential to drive innovation, it’s not a one-size-fits-all solution. Its success in fostering innovation depends on how it is used and the organisation's specific goals. Let’s explore how AI can be both a powerful tool and a potential pitfall in different innovation scenarios.

Focus on Recombination, Not Radical Reinvention

AI excels in scenarios where innovation involves recombining existing technologies rather than creating entirely new ones. This is particularly relevant in the BFSI sector, where many innovations come from improving or repurposing existing products and services.

1. Fast Response and Incremental Innovation AI can significantly speed innovation by allowing companies to iterate rapidly on existing products. For example, Moderna'’s use of AI during the COVID-19 pandemic enabled the company to develop vaccine candidates quickly and safely, demonstrating the power of AI in fast-tracking product development.
   • BFSI Example: A global bank implemented AI-driven customer service chatbots to enhance its existing online banking platform. By continuously analysing customer interactions and feedback, the bank could improve the chatbot’s performance incrementally, resulting in higher customer satisfaction and reduced operational costs.
   • Actionable Insight: BFSI companies should use AI to enhance and refine existing products, enabling them to respond quickly to market changes and customer needs.


2. Contextual Adaptation AI can help companies adapt to changing business contexts by providing insights that guide product evolution.
   • BFSI Example: A significant insurance provider used AI to adjust its underwriting processes as the gig economy grew. By analysing data on gig workers, the company developed new insurance products tailored to this growing segment's unique risks and needs, positioning itself as a leader in a rapidly changing market.
   • Actionable Insight: BFSI leaders should leverage AI to continuously adapt their products and services to evolving market conditions, ensuring they remain relevant and competitive.


3. Combinatoric Explosion In industries with many potential product variations, AI can help companies efficiently explore and evaluate these combinations.
   • BFSI Example: A financial services firm used AI to develop investment products by analysing vast market data, customer preferences, and economic indicators. The AI system identified optimal combinations of assets for different market conditions, enabling the firm to offer tailored investment portfolios that outperformed traditional offerings.
   • Actionable Insight: BFSI companies should use AI to navigate complex decision-making processes, helping them identify the best combinations of products and services to meet customer needs.

The Limits of AI in Innovation

While AI can be a powerful tool for innovation, it’s unsuitable for every innovation effort. In particular, AI is less effective in scenarios requiring radical innovation - creating entirely new products or services with no precedent.

1. The Pitfalls of AI in Radical Innovation Radical innovation often requires a level of creativity and intuition that AI cannot replicate.
   • BFSI Example: A financial institution attempted to use AI to develop an entirely new form of cryptocurrency, hoping to disrupt the market. However, the AI-based approach failed to account for the nuanced socio-economic factors that influence the adoption of new currencies, leading to a technically sound but commercially unsuccessful product.
   • Actionable Insight: BFSI leaders should recognise AI's limitations in driving radical innovation. While AI can assist in incremental improvements and recombination, breakthrough innovations often require human creativity and insight.

How to Apply AI to Innovation Processes

To effectively leverage AI in your company's innovation efforts, consider the following questions:

• Are You a Fast Follower? If your company excels at improving existing products, AI can help you optimise and refine these offerings. Focus on using AI to enhance your core competencies and accelerate time-to-market.
• Are You Struggling with Data Overload? AI can help synthesise vast amounts of data from diverse sources, enabling you to identify new opportunities and trends. Invest in AI technologies that can manage and interpret complex datasets, providing valuable insights that drive innovation.
• Are You Overwhelmed with Choices? AI can help you evaluate multiple options and combinations, helping you make informed decisions. Develop AI-driven decision-making tools to support your innovation efforts and ensure you explore all possible avenues efficiently.
• Do You Depend on Radical Innovation? AI may not be the best tool if your success hinges on breakthrough innovations. Instead, AI can be used to build on radical innovations once they are established, combining new ideas with existing knowledge to create further value.

Conclusion: AI Is a Tool - How You Use It Matters

AI is a promising tool for driving innovation, but it’s not a panacea. Success depends on how organisations use AI, particularly in the BFSI sector, where innovation is necessary and challenging. By focusing on recombination rather than radical reinvention, BFSI companies can leverage AI to enhance their existing products, adapt to changing market conditions, and navigate complex decision-making processes.

However, it’s essential to recognise AI's limits. In scenarios that require radical innovation, human creativity and insight remain irreplaceable. By understanding where AI can add value and where it cannot, BFSI leaders can strategically implement AI to drive meaningful and sustainable innovation.