2 weeks ago
AI won't scale without trusted data, says Infosys executive
A big company called Infosys helps other companies use artificial intelligence, which we call AI.
A leader at Infosys named Joydeep Mukherjee says AI works best when it has good, trustworthy information to learn from.
Only about 13 out of every 100 companies are confident that their information is ready for AI.
That means many companies need to organise their data before they can use AI well.
AI can do some jobs much faster, like finding the cause of a computer problem in one day instead of five days.
It can also help with tasks such as checking insurance claims and stopping fraud at banks.
But people still need to check the AI's work and make the final decisions.
Mukherjee says keeping information safe from hackers must be part of the plan from the start.
Most companies worry about AI risks, but very few meet the highest safety standards yet.
So the article tells companies to prepare their data carefully and keep humans in charge.
Joydeep Mukherjee, executive vice-president of Infosys, says the biggest barrier to enterprise AI adoption is access to trusted, well-governed data, not model capability.
Infosys Knowledge Institute research found only 13% of organisations are confident in their data foundations.
AI is compressing the analytics lifecycle, automating data discovery, pipeline creation, documentation, insight generation and reporting.
Recommended AI agent use cases include insurance claims processing, banking fraud management, manufacturing supply-chain exception handling and price-pack optimisation.
Research found 86% of enterprises expect heightened AI risks, while only 2% meet responsible AI gold standards.
- Who
- Joydeep Mukherjee, executive vice-president and global head of data & analytics, Infosys
- What
- Discussed how trusted, well-governed data, AI agents and governance are key to scaling enterprise AI
- Where
- Not specified in the article
- When
- Not specified in the article
- Why
- To highlight that data readiness, security and value tracking are the real gating factors for AI adoption at scale
Key facts
- Executive
- Joydeep Mukherjee
- Company
- Infosys
- Role
- Executive Vice-President & Global Head, Data & Analytics, Digital and Creative Services
- Organisations confident in data foundations
- 13%
- Enterprises expecting heightened AI risks
- 86%
- Enterprises meeting responsible AI gold standards
- 2%
- AI time-saving example
- Root-cause analysis cut from five days to one day
- Responsible AI cornerstones
- Trust, ethics, privacy, security, compliance




