How generative AI and agentic AI redefine business operations

As AI moves from pilot projects to production-scale deployments, organizations are beginning to realize measurable returns.

The Capgemini Research Institute’s new report, AI in action: How gen AI and agentic redefine business operations, explores how gen AI and agentic AI systems are transforming business operations across supply chain, finance, customer service, and people operations. From cost savings to faster decision-making, AI is reshaping the way enterprises operate.

Why AI in business operations matters today

Enterprises worldwide are scaling AI from experimental proofs of concept to full-scale business operations. The results are striking:

• Organizations are achieving an average ROI of 1.7x from AI investments.
• 40% of organizations expect positive ROI within 1-3 years, and another 35% within 3–5 years.
• Companies report 26–31% cost savings across finance, procurement, people operations, and customer service.

AI is delivering operational efficiency, faster decision-making, and tangible cost benefits – making it one of the most critical levers for business transformation.

What are Generative AI and agentic AI?

To understand their impact, it’s important to define the technologies driving this shift:

• Artificial intelligence (AI): Encompasses machine vision, natural language processing (NLP), decision-making, and automation.
• Generative AI (Gen AI): Uses large-scale data and transformer models to generate text, images, and video — enabling creativity and reasoning at scale.
• AI agents: Autonomous software that can perceive, reason, and act to achieve goals with minimal human input.
• Agentic AI: Deployment of AI agents in real-world environments, where they make independent decisions and deliver business outcomes without constant supervision.

Together, these technologies are revolutionizing workflows, embedding intelligence into everyday operations, and enabling smarter collaboration between humans and machines.

Executive insights: AI as a growth engine

The research shows a strong shift from experimentation to execution:

• Rapid adoption: In 2025, 36% of organizations deployed Gen AI (up from 20% in 2024).
• AI agents scaling fast: Usage of multi-agent systems has doubled — 21% of enterprises are already using them.
• Investment momentum: 62% of organizations increased Gen AI budgets in 2025; 36% allocated dedicated capital.
• Model preferences: 77% of executives favor proprietary AI models (from hyperscalers or niche developers) due to performance, security, and integration advantages.

Business leaders no longer see AI as an experiment — it is being positioned as a strategic enterprise asset.

Key business benefits of AI in operations

AI adoption is no longer about experimentation – it is delivering measurable business value. From reducing costs to driving ROI and enabling faster, smarter decisions, AI is reshaping the foundations of modern enterprises.

1. Strong ROI and cost efficiency

One of the most compelling benefits of AI in operations is its ability to generate immediate and measurable returns.

• Organizations report an average ROI of 1.7x on AI and Gen AI investments.
• Cost reductions of 26–31% are being achieved across core business functions such as supply chain, finance, HR, and customer operations.
• Executives also highlight 10–20% improvements in key performance metrics including accuracy, productivity, customer satisfaction, and time-to-market.

Unlike many technologies that either reduce costs or drive growth, AI delivers both top-line and bottom-line impact simultaneously — making it one of the rare enterprise technologies that pays for itself quickly.

ROI at a glance:

Figure: Average ROI from AI and Gen AI investments across supply chain, finance, HR, and customer operations (Capgemini Research Institute, 2025).

This chart shows how different functions benefit:

• People operations (HR): Highest ROI at 2.1x, thanks to automation in recruitment, training, and engagement.
• Supply chain & finance: Solid ROI of 1.5x, with major savings from logistics optimization and compliance automation.
• Customer operations: ROI of 1.7x, driven by self-service, chatbots, and AI-powered customer support.

Together, these gains reinforce AI’s role as a profitability multiplier for enterprises.

2. Sector-Specific impact

AI impacts each function differently, depending on where automation, prediction, and intelligence bring the most value.

Supply chain and procurement

• Route optimization and warehouse redesign have reduced logistics costs by 23%.
• AI-driven demand forecasting improved accuracy by up to 85%, lowering inventory costs by 15%.
• Enterprises are using AI for dynamic supplier negotiations and risk management, building resilient supply chains.

Finance and accounting

• Automated audit compliance reduced record-to-analyze costs by 25%.
• Fraud monitoring systems powered by AI improved risk detection by 75%, reducing financial exposure.
• Expense automation freed finance staff from repetitive tasks, redirecting them toward strategic planning.

People operations (HR)

• H&M’s case study shows Gen AI cut time-to-hire by 43% and reduced attrition by 25%.
• Smart résumé analysis and talent screening lowered personnel costs by 15%.
• AI-driven engagement analytics improve workforce morale, ensuring higher productivity and satisfaction.

Customer operations

• AI chatbots and automated responses reduce operational costs by 22% by handling FAQs, order queries, and troubleshooting.
• Telstra’s Gen AI assistants enabled 90% of employees to save time and deliver faster, better service.
• Personalized recommendations and sentiment analysis improve customer loyalty and long-term revenue.

Together, these use cases demonstrate that AI is not confined to back-end operations but is equally transformative in customer-facing processes.

3. Faster decision-making and risk mitigation

Beyond efficiency and savings, AI provides organizations with real-time intelligence and predictive insights.

• Finance teams leverage AI to predict cash flow, identify anomalies, and flag fraud before it happens.
• Supply chains benefit from AI models that anticipate demand spikes, optimize routing, and mitigate risks from supplier disruptions.
• Customer operations use AI for proactive issue resolution – detecting early service problems and preventing escalations.

This ability to move from reactive to proactive decision-making strengthens business resilience, especially in volatile markets. Organizations that embed AI into their decision frameworks gain not just speed, but also greater accuracy, reduced risk, and higher agility.

Six steps to building AI-driven business operations

To scale AI successfully, organizations need a structured approach:

1. Build AI readiness: Strong leadership, governance, and data foundations accelerate ROI 45% faster.
2. Develop workforce AI skills: Equip employees to work with AI, reduce resistance, and foster collaboration.
3. Redesign processes: Re-engineer workflows to embed AI where it adds the most value.
4. Embrace agentic AI: Deploy autonomous AI agents for decision-making, compliance, and customer support.
5. Maintain cost discipline: Track cost per inference, scalability, and ROI to ensure sustainable adoption.
6. Scale strategically: Balance build vs. buy decisions, ensuring long-term adaptability.

This roadmap transforms AI from a tool into a strategic advantage.

Industries leading the AI revolution

Certain sectors are leading AI adoption due to clear use cases and competitive pressures:

• Consumer products: 73% of organizations increased Gen AI investments in 2025.
• Banking & insurance: Heavy AI use in compliance, fraud monitoring, and risk analysis.
• High-Tech: 45% adoption of AI agents, the highest across industries.
• Manufacturing & utilities: Using AI for predictive maintenance, workforce optimization, and supply chain resilience.

This shift highlights a move toward industry-specific AI models — with 50% expected to be domain-specific by 2027.

Preparing for the future: What’s next in AI for business

Looking ahead, the AI landscape is set to evolve rapidly:

AI in business operations is no longer a future concept. It is here, delivering ROI, cost savings, efficiency, and customer value at scale.

Organizations that act decisively today – investing in data, governance, workforce readiness, and agentic AI – will be the ones leading tomorrow’s markets.

The message is clear: the sooner organizations prepare, the stronger their competitive advantage will be.

How Capgemini can help

At Capgemini, we help organizations move beyond AI experimentation to deliver real business impact at scale. Our expertise in generative AI, agentic AI, intelligent process automation, and data-driven transformation enables enterprises to unlock measurable ROI, reduce operational costs, and build future-ready business models. From designing AI strategy and governance frameworks to deploying industry-specific AI use cases across supply chain, finance, customer service, and people operations, Capgemini empowers organizations to accelerate adoption while ensuring trust, security, and scalability. With our proven methodologies and deep industry knowledge, we partner with leaders to turn AI into a competitive advantage and a driver of sustainable growth.