TECHNOLOGY efficiency gains. Not because the AI is exceptional in isolation, but because it understands the procurement workflow at those specific organisations.
Q. YOU MENTIONED KNOWLEDGE GRAPHS AS PART OF THIS. THAT’ S NOT A TERM MOST EXECUTIVES LEAD WITH. WHY DOES IT MATTER?
» At its heart, Evalueserve has always been a knowledge management company. We’ ve been doing that for 25 years. So this isn’ t a new direction for us, it’ s the foundation we’ ve been building on the whole time.
AI is only as good as its understanding of the relationships between things. In knowledge-intensive industries, context is everything. A term in a regulatory submission means something different depending on the therapy area, the market and the health authority. A supplier risk flag means something different depending on where it sits in the supply chain.
Knowledge graphs are how you encode that relational understanding in a way the AI can use. It’ s not a new concept, but it’ s becoming essential as AI systems take on more complex, multi-step work. If you don’ t have that layer, you end up with AI that’ s confident but wrong, which is worse than AI that’ s appropriately uncertain.
We think of knowledge management as foundational infrastructure, not a nice-to-have. The organisations that build it properly now will have a compounding advantage. The ones that skip it will keep wondering why their AI programmes aren’ t delivering.
“ At its heart, Evalueserve has always been a knowledge management company”
Pallab Deb CEO Evalueserve
Q. WHAT’ S YOUR ADVICE FOR ENTERPRISE LEADERS TRYING TO FIGURE OUT WHERE TO START?
» Find the workflow where the cost of getting it wrong is highest, and where you have someone who deeply understands how it works. That combination tells you where domain-led AI has the most leverage. Don’ t start with the technology. Start with the work. Ask: where is the cognitive load on our best people highest? Where does a mistake cost real money or real time? Where would a 40 % improvement in speed change something meaningful for the business? That’ s where to focus first.
And be honest about what you actually have. Most organisations overestimate their data readiness and underestimate the domain knowledge required. The faster you close that gap on the domain side, the faster the AI starts doing something useful.
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