Korn Ferry's 2026 report: 79% of Indian employees are more productive with AI, yet 78% report heavier workloads. What L&D and managers should do.
Key takeaways
- Korn Ferry's Workforce 2026 survey covered more than 16,000 professionals in 11 markets, including about 2,000 in India. The India findings were released on 30 September 2026 (ANI, ThePrint).
- India is ahead of the global average on AI: about 86% are positive about how AI will change their work (65% globally), and about 76% feel adequately trained (52% globally).
- The cost shows up in workload: about 79% say they are more productive, yet about 78% report significantly higher workloads over two years (62% globally), and about 73% say AI has increased the number of tasks expected of them.
- About 72% of Indian respondents say they now do the work of more than one role.
- First-level managers are squeezed hardest: about 80% report significantly higher workloads and 76% say AI has added tasks.
- Efficiency is not the same as capacity. Unless leaders decide what happens to saved time, it disappears into new demands.
Last updated · Bodhih Insights team · reviewed by Siddharthan VGJ, Founder
Here is what 2,000 Indian professionals told Korn Ferry in 2026: they are more productive than a year ago, they like AI, they feel trained to use it, and their workloads have grown sharply anyway. The time AI saved did not return to them. It was spent, by someone else, on more work.
That tension is the most useful finding in the consulting firm's Workforce 2026 report, and it explains a lot about why some AI programs feel like a success on the dashboard and a strain on the floor.
A note on sources: figures come from Korn Ferry's press release as published by ANI and other outlets. Some outlets mix global and India numbers, so we used the India-labelled figures and flagged global comparisons. We have not reviewed the full report; check it before quoting externally.
The Numbers Tell Two Stories at Once
Read the India results one way and they are a triumph. Read them another way and they are a warning.
The triumph. Indian employees are more positive about AI than their global peers (about 86% against 65%). They are more likely to say AI is built into how their role works (about 73% against 54%). And far more of them say they have been adequately trained (about 76% against 52%). By the usual adoption measures, this is a workforce that has done what leaders asked.
The warning. The same people report workloads that have risen significantly (about 78% against 62% globally), more tasks per role (about 73%), and responsibility for more than one job (about 72%). Around 70% also say AI fluency is now being built into performance reviews, against about 50% globally. So AI is both a helper and a new yardstick.
Put together: employees are faster, trained and willing, and the bar has moved up with them.
Where Did the Saved Time Go?
When a task that took two hours takes thirty minutes, one of four things happens:
- The person keeps the time for thinking, learning or rest.
- The person is given more tasks of the same kind.
- The role is widened to cover work that used to belong to someone else.
- The team shrinks, and the remaining people absorb the work.
The Korn Ferry numbers suggest options 2 and 3 are common. This is not a conspiracy. It is how organisations behave by default. Nobody decides to remove the slack; the freed time is simply the easiest place to put the next request.
There is also a perception gap at the top. Globally, coverage of the report notes that about 79% of CEOs say they see AI efficiency gains, against about 51% of individual contributors (Middle East AI News). Leaders see the output curve rise. Employees feel the effort curve rise with it.
Why This Is a Training Problem, Not Only a Workload Problem
It is tempting to file this under "HR wellbeing" and move on. Most of it is really about skills that no AI course teaches.
- Prioritising when everything is faster. If every task is quicker, the number of things you can do explodes. Deciding what should be done is a judgement skill, and it is rarely trained.
- Saying no, or "not yet", with evidence. Employees who cannot negotiate scope end up with a widened role by default.
- Checking AI output efficiently. Time saved on drafting is lost again on fixing weak output. We explored this in Workslop and in AI brain fry.
- Managers who can protect capacity. First-line managers are carrying the heaviest load and are the ones who translate "AI efficiency" into team targets. Our post on the disengaged manager shows what that squeeze does to engagement.
- Noticing silent strain. A busy, productive, smiling team can still be coming apart. See quiet cracking.
The Retention Risk Nobody Has Priced
Overloaded people do not always complain. Some of them stay put and disengage; some leave when the market turns. We wrote about the first pattern in job hugging. If AI-driven workload growth sits on top of that, a company can look stable on attrition while its best performers quietly stop giving extra effort.
Six Moves for L&D, HR and Business Leaders
- Decide in advance what saved time is for. Before rollout, state where freed hours should go: quality, learning, customer time, or growth work. If you do not decide, demand will.
- Track workload, not only adoption. Add questions on task volume, role scope and overtime to your AI pulse surveys. Report them next to usage numbers.
- Audit role creep. Compare job descriptions with what people actually do. Where roles have doubled, re-scope, re-grade or add headcount.
- Train prioritisation and boundary-setting. Pair AI tool training with sessions on scoping, delegating, and pushing back with data. Bodhih's time management and workplace resilience content is built for this.
- Equip first-line managers first. Give them a simple capacity conversation guide: what is on the plate, what AI changed, what can be dropped. First-Time Manager Training is a natural starting point.
- Be careful with AI fluency in reviews. If 70% of employees believe AI use is being scored, they will perform it. Define what good looks like (accuracy, judgement, outcomes) rather than rewarding volume.
How Bodhih Helps
Bodhih designs programs that connect AI adoption to the human skills that make it sustainable.
- AI Literacy Training teaches people to use AI tools with judgement, including how to check and improve output.
- Leading Human + AI Teams Training helps managers set realistic expectations, protect capacity and review shared human and AI work.
- Workplace Resilience Training and Resilient Leadership Training build the habits that keep fast-moving teams healthy.
- Skill gap analysis and assessments show where capability is strong and where people are covering gaps through extra hours.
Corporate batches are private and tailored to your roles and tools. Open workshops are fixed-date public batches.
The Bigger Idea
For two years the question about AI at work was "will people adopt it?" India has answered with a loud yes. The next question is less comfortable: who benefits when they do?
If the answer is "the plan, the dashboard and the next quarter's targets", the gains will last only as long as people's patience. If the answer includes the employee, in time, focus or growth, AI becomes something people want to keep using. That choice is a leadership decision, and a trainable one.
Frequently asked questions
What does the Korn Ferry Workforce 2026 report say about India?
Based on the India release of 30 September 2026, about 79% of Indian employees say they are more productive than a year ago, about 78% report significantly higher workloads over two years, about 73% say AI has increased the tasks expected of them, and about 72% perform more than one role (ANI).
Does AI actually increase workload?
It can. AI speeds up individual tasks, but organisations often respond by adding tasks or widening roles. Korn Ferry's data suggests that for many employees, efficiency gains turned into higher expectations rather than free time.
How can companies stop AI efficiency turning into overload?
Decide in advance how saved time will be used, track workload alongside AI adoption, audit role creep, and train managers to run capacity conversations with their teams.
Why are first-level managers affected most?
They translate organisational targets into team work while also doing their own tasks. In the Korn Ferry India data, about 80% of first-level managers reported significantly higher workloads and about 76% said AI had added tasks.
What training helps with AI-driven workload?
Programs on AI literacy, prioritisation and time management, workplace resilience, and people-manager skills. See Bodhih's AI Literacy Training, Workplace Resilience Training and First-Time Manager Training.
Where do the facts in this article come from?
Survey figures are from Korn Ferry's Workforce 2026 report as published by ANI, ThePrint and Middle East AI News. We have not reviewed the full report.
