Infosys, India’s second-largest IT services company, has launched AI innovation labs and AI factories to drive the development and deployment of artificial intelligence solutions across industries. These initiatives aim to incubate, validate, and scale AI-driven innovations, working in collaboration with clients to enhance business efficiencies.
As AI adoption accelerates, enterprises are under increasing pressure from boards and executives to showcase tangible AI capabilities, particularly in generative AI (Gen AI) and Agentic AI. Infosys’ latest efforts underscore the growing significance of data readiness, business process transformation, and AI-driven automation in shaping the future of enterprise operations.
AI Innovation Labs: Driving Proof of Value for Emerging Technologies
The AI innovation labs at Infosys are designed to track, assess, and develop proof of value for emerging AI technologies before they are implemented at scale. By collaborating with clients, the labs help businesses evaluate AI solutions that align with their industry-specific challenges.
According to Rafee Tarafdar, Chief Technology Officer at Infosys, AI use cases are already delivering measurable impact across organizations. A recent Infosys research report revealed that:
Over 50% of AI implementations are yielding measurable business impact.
19% of AI solutions fully meet their intended objectives, while another 32% show promise by partially meeting them.
Highlights:
Infosys AI labs focus on proving the business value of AI applications before scaling.
More than half of AI projects are already generating measurable returns.
A structured approach to data architecture is crucial for AI success.
AI Factories: Scaling Solutions Across Business Lines
Beyond research and proof-of-value experiments, Infosys has also established AI factories to productize and scale AI solutions across industries. These factories act as hubs where validated AI solutions are industrialized and deployed at scale for clients.
The AI factory model allows Infosys to optimize AI models through continuous improvements, ensuring that businesses can integrate AI into their workflows seamlessly. Data readiness is a key factor in enabling this transformation, as companies need robust data architectures to leverage AI effectively.
“We see that a significant effort has to be spent in this space, and at Infosys, we have a data readiness for AI framework that is helping our clients transition to the right architecture,” Tarafdar stated.
Highlights:
AI factories transform proof-of-value concepts into scalable business solutions.
Continuous improvements and human feedback loops enhance AI model accuracy.
Robust data architectures are essential for unlocking AI’s full potential.
Sectors Leading AI Adoption and Use Cases
As AI integration deepens across industries, certain sectors are emerging as early adopters of AI-driven transformation. Infosys has identified services, hi-tech, telecommunications, life sciences, financial services, and logistics as the most active industries in AI deployment.
Currently, the most prominent AI use cases are seen in:
Software engineering – AI-assisted code generation and optimization.
Business and IT operations – AI-powered automation for process efficiency.
Fraud risk and compliance – AI-driven anomaly detection and risk assessment.
Cybersecurity – AI-enhanced threat detection and mitigation.
Customer service – AI chatbots and personalized customer support solutions.
Finance – AI-assisted credit risk decisioning and investment research.
Highlights:
AI adoption is strongest in IT, finance, telecom, and logistics sectors.
Software engineering and cybersecurity are among the top AI-driven business functions.
AI is playing a crucial role in automating compliance, fraud detection, and risk management.
Challenges in AI Adoption: Change Management and Workforce Training
While AI is gaining traction across enterprises, a major roadblock remains: organizational readiness for AI-driven change. Infosys’ latest research highlights that:
Only 16% of companies have implemented effective change management and workforce training for AI adoption.
Many organizations struggle with aligning AI investments to measurable business outcomes.
Tarafdar emphasized the need for regular evaluation of AI investments to ensure they are aligned with evolving business goals. Infosys has been leveraging a proof-of-value approach to assess AI effectiveness before full-scale deployment.
“The accuracy of Gen AI solutions is constantly improving with better model releases and human feedback loops refining them further,” he added.
Challenges:
Change management and employee training gaps are slowing AI adoption.
Regular reviews of AI investments are critical to ensure business value.
Human feedback remains vital for refining AI-generated outputs.
Agentic AI: The Next Leap in AI Autonomy
Among the latest advancements in AI, Agentic AI is emerging as a transformative force in enterprise automation. Unlike traditional AI, which operates within predefined rules, Agentic AI possesses decision-making, reasoning, and autonomous execution capabilities, making it a game-changer for business operations.
Infosys has accelerated Agentic AI adoption across its client base, integrating it into areas such as:
Deep research for customer service – AI-powered knowledge discovery and response automation.
Financial auditing – AI-driven transaction analysis and anomaly detection.
eKYC (electronic Know Your Customer) verification – AI-assisted customer onboarding and compliance checks.
Credit risk decisioning – AI-powered financial assessments for lending.
Investment banking research – AI-driven market trend analysis.
Software engineering lifecycle – AI-augmented coding, testing, and debugging.
IT operations and cybersecurity – AI-enhanced system monitoring and threat detection.
Agentic AI vs. Traditional AI:
Traditional AI – Operates based on pre-set rules and inputs, requiring human intervention.
Agentic AI – Autonomously plans, decides, and executes tasks with minimal human involvement.
Infosys’ AI research suggests that Agentic AI will play a key role in future enterprise workflows, reducing the need for manual decision-making while increasing operational efficiencies.
Developments:
Agentic AI enables businesses to automate decision-making and execution.
Infosys is actively integrating Agentic AI across financial services, IT operations, and security domains.
This next-gen AI technology is expected to redefine how enterprises handle automation.
The Road Ahead for AI in Enterprise Digital Transformation
With Infosys doubling down on AI innovation labs, AI factories, and the adoption of Agentic AI, enterprises are poised for a new era of AI-driven transformation. However, success will hinge on factors like data readiness, change management, and continuous AI optimization.
As companies look to navigate rapid AI advancements, Infosys’ approach of incubating AI innovations, validating their impact, and scaling them strategically positions it as a frontrunner in the enterprise AI revolution.
