Genpact and HFS Research: 92% of Executives Say Agentic AI Will Fundamentally Change Business Operations

Genpact (NYSE: G) and HFS Research report finds 92% of 545 senior executives expect agentic AI to fundamentally change work execution, while organizational readiness remains the main barrier.

Rhea-AI Summary

Genpact (NYSE: G) and HFS Research report finds 92% of 545 senior executives expect agentic AI to fundamentally change work execution, while organizational readiness remains the main barrier. Investment in agentic AI is forecast to rise 38% next year, yet 33% cite unprepared processes and only 22% are comfortable granting broad autonomy.

The study highlights gaps in accountability, measurement, people, and process and recommends four actions to scale autonomous execution within ~17 months on average.

Positive

• 92% of executives expect agentic AI to change work execution
• Projected investment increase of 38% in the next year
• Average enterprise expects to scale agentic AI in 17 months
• Clear four-action framework: accountability, measurement, people, process

Negative

• Only 22% comfortable granting broad autonomy to AI agents
• Nearly 80% of systems run in supervised modes with human final approval
• 67% rely on outdated productivity metrics for autonomous outcomes
• 33% say unprepared business processes are the top adoption obstacle

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Details

News Market Reaction – G

On Apr 29, the day this news came out, G closed 0.21% below the previous close.

Data tracked by StockTitan Argus for the Apr 29 session.

Market Context

This announcement underscores Genpact’s focus on agentic AI and organizational readiness, based on a...

Analysis

This announcement underscores Genpact’s focus on agentic AI and organizational readiness, based on a survey of 545 executives across 11 industries. It highlights that 92% expect agentic AI to change work, yet only 22% are comfortable granting broad autonomy, with process readiness and governance as key barriers. In context, Genpact has repeatedly issued AI-themed updates with modest average share moves of 0.58%, suggesting a longer-term positioning story rather than an immediate financial catalyst.

Key Figures

Survey respondents: 545 senior executives Industries covered: 11 industries Believe AI changes work: 92% of respondents +5 more

Survey respondents

545 senior executives

Cross-industry agentic AI study sample size

Industries covered

11 industries

Scope of agentic AI adoption survey

Believe AI changes work

92% of respondents

View that agentic AI will fundamentally change work execution

Operate in supervised mode

nearly 80% of organizations

Keep humans as final approval over most AI actions

Comfort with broad autonomy

22% of organizations

Comfort granting AI agents broad autonomy

Investment increase

38% projected rise

Expected increase in agentic AI spending in next year

Time to scale AI

17 months

Average timeframe to scale agentic AI

Process readiness barrier

33% of respondents

Cite unprepared business processes as top obstacle

Previous AI Reports

5 past events · Latest: Apr 08

Same Type 5 events

1. Apr 08

   AI partnership update

   24h Move

   -1.5%

   Partnership to embed AI-native web agents and Task API in architecture.

2. Jun 24

   AI product launch

   24h Move

   +1.7%

   Launch of agentic AI AP Suite for accounts payable automation.

3. Jun 10

   AI insurance study

   24h Move

   +0.9%

   Research with AWS on AI adoption gaps in insurance and customer impact.

4. Apr 29

   AI customer research

   24h Move

   +1.3%

   Study on insurance customers’ willingness to embrace AI when value clear.

5. Apr 22

   AI leadership ranking

   24h Move

   +0.4%

   Named Leader in NelsonHall 2025 NEAT for P&C analytics and AI.

24h Move is the share-price change in the day after each event; other market factors may also have contributed.

Key Terms

agentic ai, autonomous execution, ai agents, kpis, +1 more

5 terms

agentic ai technical

"Genpact (NYSE: G), an agentic and advanced technology solutions company..."

Agentic AI refers to computer systems that can make their own decisions and take actions without needing someone to tell them what to do each time. It's like giving a robot a degree of independence to solve problems or achieve goals on its own, which matters because it could change how we work and interact with technology in everyday life.

autonomous execution technical

"shift AI from a productivity tool to an autonomous execution layer within the enterprise"

Autonomous execution is when computer programs automatically place and manage buy or sell orders in financial markets without direct human control, acting like a self-driving car for trades. It matters to investors because it can execute orders faster and at lower cost, reduce human errors, and respond to market moves instantly, but it can also amplify losses or market volatility if the software misbehaves or encounters unexpected conditions.

ai agents technical

"Only 22% of organizations are comfortable granting AI agents broad autonomy."

AI agents are computer programs designed to perform tasks or make decisions automatically, often by learning from data and adapting to new information. They act like virtual assistants or robots that can handle complex activities without human intervention, which can help businesses and individuals save time and improve efficiency. For investors, AI agents matter because they can enhance decision-making and automate processes that influence markets and financial outcomes.

kpis financial

"Measurement: Adopting agent-native KPIs that track outcomes such as autonomous workflow completion."

Key performance indicators (KPIs) are specific, measurable metrics a company uses to track how well it is reaching important goals, like sales growth, profit margins, customer retention, or production speed. They matter to investors because KPIs act like a company’s dashboard gauges—showing whether management’s strategy is working, signaling trends or problems early, and helping predict future earnings and risks that affect the value of an investment.

workflow orchestration technical

"skills in demand today are ... workflow orchestration and integration (42%), data engineering..."

Workflow orchestration is the automated coordination of a series of tasks and systems so work happens in the right order, at the right time, without manual intervention — like a conductor ensuring each musician comes in on cue. For investors, it matters because better orchestration can cut costs, speed up operations, reduce errors and compliance risk, and make a business easier to scale and measure, all of which can affect profitability and reliability.

AI-generated analysis. How Rhea-AI works. Not financial advice.

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Investment in agentic AI is projected to rise 38% in the next year, but organizational readiness – not technology – is the primary barrier to scale

NEW YORK, April 29, 2026 /PRNewswire/ -- Genpact (NYSE: G), an agentic and advanced technology solutions company, today released a new research report with HFS Research, Autonomy Requires Trust in AI, that reveals a significant gap between agentic AI ambition and organizational readiness. The study explores the key barriers enterprises face when scaling agentic AI to uncover the foundational elements required to shift AI from a productivity tool to an autonomous execution layer within the enterprise: accountability, measurement, people, and process.

The research, based on a survey of 545 senior executives across 11 industries and interviews with leaders from Fortune 2000 companies, found that 92% of respondents believe agentic AI – systems that can autonomously coordinate tasks and make decisions – will fundamentally change how work is executed. Despite this, nearly 80% of organizations still operate these systems in supervised modes, with humans retaining final approval over most actions.

"Enterprises have proven that generative AI can accelerate work; the next frontier is proving that agentic AI can take responsibility for executing it," said Ajay Vasal, Global Leader for Data & AI, Genpact. "This shift from assistive to autonomous AI is beyond a technology upgrade and requires a fundamental rethink of operating models. Success depends on how organizations redesign processes with accountability and decision rights built in, while properly equipping their people to ensure agentic AI operates as a true extension of human intent."

Key findings
The research points to four foundational elements determining whether agentic AI scales to autonomous execution or remains experimental:

• The trust and accountability gap: Only 22% of organizations are comfortable granting AI agents broad autonomy. The biggest barriers are not technical but center on regulatory exposure, reputational risk, lack of explainability, and unclear accountability.
• Investment rising, metrics lagging: Enterprises expect to scale agentic AI within an average of 17 months, with spending projected to increase by 38% in the coming year. However, 67% still rely on outdated productivity metrics that fail to capture the value of autonomous decision-making.
• Flatter organizations, shifting skills gap: 44% of executives expect fewer management layers as agentic AI absorbs coordination work. At the same time, the top skills in demand today are shifting from building AI to operating alongside it – workflow orchestration and integration (42%), data engineering (39%), and monitoring and observability (36%) – meaning structural redesign for autonomy is moving faster than human role design.
• Process readiness is the leading barrier: 33% of respondents cite unprepared business processes as the top obstacle to agentic AI adoption, highlighting that workflow redesign – not technology – determines how far autonomy can scale.

Four critical actions for scaling autonomy
The report identifies four key actions to move beyond experimentation to enterprise-scale autonomous execution:

1. Accountability: Defining who owns the agent's actions and failures.
2. Measurement: Adopting agent-native KPIs that track outcomes such as autonomous workflow completion.
3. People: Providing role clarity and defining new human oversight responsibilities.
4. Process: Redesigning workflows to remove manual handoffs and sequential human approvals.

"Ambition for autonomy is outpacing the ability to govern it," said Phil Fersht, CEO and Chief Analyst, HFS Research. "The leaders in agentic AI won't be the fastest adopters, they'll be the ones who redesign accountability, measurement, and human oversight so autonomy scales with control and delivers compounding value."

For more information and to download the full report, visit https://www.genpact.com/insight/autonomy-requires-trust-in-ai.

About Genpact

Genpact (NYSE: G) is an agentic and advanced technology solutions company. We leverage process intelligence and artificial intelligence to deliver measurable outcomes. With a strong partner ecosystem and decades of client trust, we provide innovative solutions that transform how businesses run. Powered by a team with an active learning mindset and client centricity at its core, we deliver lasting value for the world's leading enterprises.

Get to know us at genpact.com and on LinkedIn, YouTube, X, and Facebook.

MEDIA CONTACT:

Geraldine Lim
Genpact Media Relations 
+1-951-318-3494
geraldine.lim@genpact.com

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SOURCE Genpact

FAQ

AI-generated questions and answers. How Rhea-AI works. Not financial advice.

What did Genpact (G) and HFS Research find about executive views on agentic AI?

Most executives expect systemic change: 92% foresee agentic AI altering work execution. According to Genpact, the finding comes from a survey of 545 senior executives across 11 industries and Fortune 2000 interviews.

How much will enterprises increase spending on agentic AI, according to Genpact (G)?

Enterprises plan higher investment: spending is projected to rise 38% in the next year. According to Genpact, firms expect this increase even as many lack process and measurement readiness for autonomous execution.

What are the main organizational barriers to scaling agentic AI noted by Genpact (G)?

The primary barriers are governance and process: accountability, measurement, people, and process readiness. According to Genpact, regulatory exposure, reputational risk, explainability, and unclear ownership limit broad autonomy.

How soon do companies expect to scale agentic AI to autonomous execution per Genpact (G)?

Enterprises expect to scale agentic AI within about 17 months on average. According to Genpact, this timeline coexists with widespread reliance on supervised modes and legacy productivity metrics.

What operational changes do Genpact (G) and HFS recommend to enable agentic AI?

Four critical actions are recommended: define accountability, adopt agent-native measurement, clarify people roles, and redesign processes. According to Genpact, these steps aim to move agentic AI from experiment to enterprise-scale autonomous execution.