Research Forum: Amplifying Innovation in R&D through Artificial Intelligence
Manmit Shrimali, head honcho and innovator at Turing Labs, is leading the charge to disrupt traditional Research and Development (R&D) techniques.
In various R&D labs worldwide, hundreds of formulation scientists put in countless hours coming up with new consumer products. These teams of brilliant researchers meticulously go through iterations—testing, adjusting, and perfecting formulations.
Being in charge of a company bridging AI and R&D, I've had the chance to observe how traditional product creation can be enhanced by innovative computational methods. The tried-and-true trial-and-error process driving innovation in consumer goods is being revolutionized by the ability to explore potentials computationally before diving into the lab.
A Transformation in the CPG Sector
Across the Consumer Packaged Goods (CPG) industry, I've noticed a pattern: AI-assisted formulation platforms are helping R&D teams create successful products in half the time, while drastically reducing the number of physical experiments required. More impressively, these teams are discovering formulations that might have taken years to find using traditional methodology alone.
This evolution in R&D practices has been intriguing to observe. Traditionally, formulation scientists have spent nearly half their time designing possible recipes, carefully picking out ingredients and proportions based on their understanding of ingredient relationships and desired product attributes.
AI platforms can now generate thousands of promising formulation suggestions, freeing up scientists to focus on what they do best: identifying patterns, making informed decisions, and leveraging their extensive experience in real-world business and manufacturing constraints.
This change in focus is significant. Imagine a formulation scientist stepping into their lab in the morning. Instead of facing a blank canvas and years of hit-or-miss attempts, they're greeted with dozens of promising formulations, each validated computationally. This isn't just about efficiency—it's about using human expertise more strategically.
Human-AI Collaboration
However, the impact varies among different R&D teams. The most successful teams haven't necessarily invested in cutting-edge AI tools but rather those who excel at combining their domain knowledge with AI capabilities. Success results from creating an environment where AI and human insights constantly shape and strengthen each other, leading to discoveries that none could achieve alone.
Take, for instance, our collaboration with a personal care company developing a sulfate-free shampoo. The challenge lay in creating a formula that had rich lather while adhering to new sustainability standards. Traditional methods were struggling because the formulation space was too expansive to explore systematically; there were just too many possible ingredient combinations and concentrations to test.
AI alone might have provided numerous theoretically interesting formulas, but many would have been impractical from a manufacturing or stability standpoint. The breakthrough came from human-AI collaboration. Together, they identified a unique combination that neither would have likely discovered individually. The AI spotted subtle patterns in ingredient interactions that humans didn't noticed, while the scientists molded these insights into a commercially viable product.
The takeaways for R&D leaders are clear:
1. Promote true collaboration. Build teams where AI and human knowledge are seamlessly integrated, not just working side by side. Success relies on creating workflows where each enhances the other.
2. Protect and use domain expertise. Scientists' specialized knowledge becomes even more valuable when coupled with AI abilities. Keep investing in specialized knowledge while developing new skills in AI collaboration.
3. Revamp development processes. Traditional formulation procedures need an update to maximize the benefits of human-AI synergy. Focus on creating processes that foster continuous interaction between computational insights and human expertise.
Implementing AI Challenges
This transformation presents its obstacles. Some scientists fear their role in an AI-assisted development process. As leaders, we must help our teams understand that their knowledge is more valuable than ever—it's evolving to embrace new possibilities. The creativity now lies in how they work with AI to expand what's achievable in product development.
We've witnessed this transition process unfold repeatedly. Many R&D teams are initially hesitant to adopt new AI systems. But as they start seeing results in weeks instead of months, attitudes shift dramatically. Scientists who initially resisted change adopt AI with just as much ease as they open a spreadsheet. This shift in mindset occurs not through orders but through outcomes: When teams experience firsthand how AI strengthens their abilities, natural apprehension fades away.
The Future of R&D
Human-AI collaboration in formulation development offers distinct advantages. While AI can investigate extensive possibility spaces and recognize subtle patterns in ingredient interactions, real-world constraints like ingredient costs, manufacturing processes, and consumer preferences require the nuanced judgment of scientists. By joining forces, formidable solutions emerge.
For those managing R&D teams, the message is clear: Success isn't about choosing between human expertise and artificial intelligence but in mastering their integration. The secret lies in creating an environment where each complements the other, leading to discoveries neither could achieve individually.
I believe we're at the onset of the largest R&D revolution since the introduction of computational chemistry.
The future of innovation won't rest with companies boasting the largest R&D budgets. Instead, it will belong to those who best combine human insight with artificial intelligence and master this new way of working. They must grasp that the most significant breakthroughs stem not from AI alone but from human-AI collaboration.
That future begins now.
The Technology Advisory Council is a select gathering of elite CIOs, CTOs, and technology executives. Do I fit the bill?
Manmit Shrimali, with his innovative approach at Turing Labs, is inspiring other R&D leaders to incorporate AI into their formulation processes, just as he is doing within his team.
In the Technology Advisory Council, Manmit Shrimali could share his insights and experiences about the impact of AI on R&D, encouraging other executives to embrace this change and transform their respective industries.