The latest advances in artificial intelligence (AI) offer life sciences companies enormous potential to help patients live healthier lives. The TCS AI for Business Study shows that nearly half of senior executives in life sciences are optimistic about the potential impact of AI in their organization. The report provides this and other unique insights about how life sciences companies are moving forward to create effective AI strategies for their enterprise. This report explores:
Many life sciences executives we surveyed have a positive sentiment toward AI.
Our study shows that the majority of life sciences companies are preparing for AI or have already embarked on their AI journey.
Yet there’s no consensus on AI adoption strategies and not enough metrics to measure success with 76% saying they need better KPIs for their AI implementations.
Yet there is a gap between aspiration and reality with:
What is hampering AI progress in life sciences companies?
When it comes to concerns about AI, especially with the hype around generative AI (GenAI), five strategic challenges are top of mind for life sciences companies.
As the integration of AI into business processes accelerates, expected financial return on such an investment becomes increasingly significant. But only 20% of life sciences companies said they have "good enough" metrics and KPIs for their current stage of AI deployments.
Without adequate KPIs for AI-enabled operations, proving ROI and getting future buy-in is challenging.
Most life sciences executives believe AI will augment and enhance human capabilities, enabling people to focus on higher-value activities that require creativity, empathy, and strategic thinking.
72% think human strategic decision-making and creativity will remain essential to their competitive advantage.
As AI becomes more advanced and part of “business as usual,” the role of humans in the workplace will evolve. Within the next three years, 48% of life sciences companies expect most of their employees will be using GenAI on a daily basis.
Innovation and revenue growth will be a focus for future AI implementations. 61% of Pacesetters in life sciences—the more financially successful companies we surveyed—are primarily focused on using AI to spur innovation.
Get started. Focus on a few use cases to begin with. Identify those low-hanging fruits, which will help you to demonstrate the value of AI early on in your pilot phase. This will enable you to gain the buy-in of your business stakeholders. Don’t linger on an idea for too long. Try to take it into production to gain the first-mover advantage.
It is important to understand that AI transformation cannot be one size fits all. It will have to be contextualized according to the business scenario and intended outcome. Ensure that the implementation is flawless before eyeing effectiveness. Be open to initiatives that are focused not only on productivity, but also on revenue multiplier opportunities.
Not everything needs AI. Weigh ROI vis-a-vis total cost of ownership and carefully choose areas for AI implementation. Like with any other technology, monitor usage by business units and functions with a consumption tracker and distribute costs as per usage. Based on the outcome evaluation, know the focus areas to sustain or stop AI implementation.
Collaborate with partner ecosystems in the areas of accessing specialized expertise and talent, technology and resource sharing and innovation, to accelerate and enhance scaled AI adoption. Strike a balance between building the in-house AI talent and expertise and utilizing specialists from technology partners.
To harness AI responsibly, CMI enterprises need to build an AI governance framework covering fairness and transparency, ethical principles, security and privacy standards, observability, governance and risk management and regional and telecom industry regulatory controls. This ensures AI is used ethically and delivers value for both the organization and the society.
TCS’ Thought Leadership Institute conducted an anonymous study of approximately 1,272 senior executives with P&L responsibilities in 12 industry sectors across Asia, Europe, Nordics, LATAM, North America, and the United Kingdom and Ireland, with respondents having an annual revenue of $5 billion to $100 billion. The life sciences industry findings are based on feedback received from 90 survey respondents.
This global study examines how CEOs, LOBs, directors, and business line managers are preparing their business to be AI-ready, focusing on aspects such as their strategy around operations, talent, and future implementation plans. The study also provides best practice recommendations based on these insights.
