Business Models and Technology Strategies to Capitalize on Autonomous AI Agents
Agentic AI is more than just the next wave of automation — it represents a seismic shift in how businesses operate, compete, and create value. Unlike traditional AI that waits for instructions, agentic systems can independently set goals, design solutions, and execute tasks, acting as intelligent collaborators in everything from customer service to supply chain management. Because of this, major technology providers, cloud hyperscalers, and startups are racing to build intelligent platforms, multi-tool orchestration layers, and marketplace ecosystems that strengthen the foundation of AI agents.
Now, as AI evolves into proactive, contextual systems, it opens up new possibilities: autonomous financial advisors, AI-first logistics, intelligent virtual assistants, and more. The business case is compelling. Agentic AI can unlock operational efficiency, increase workplace productivity, enable large-scale personalization, and support new business models like outcome-based pricing or AI-as-a-service. However, integration hurdles, skill gaps, fragmented technology stacks, and security concerns remain real challenges — Which technologies and partnerships will help you address implementation challenges in agentic AI?
Webinar Highlights
- Technology Adoption: Deployment strategies for AI agents and the current state of adoption.
- Growth Barriers: How to address challenges like enterprise integration, skill gaps, AI governance, and security risks.
- Opportunity Evaluation: Emerging business models and growth prospects for stakeholders — from pre-built agentic AI solutions to agent lifecycle management.
Frost & Sullivan’s latest ICT webinar shed light on Growth Strategies to Make the Most of Agentic AI. Through real-world examples and strategic insights, this webinar explored the evolving AI ecosystem, common missteps, and emerging opportunities in agentic AI.
Featured Experts:
Here, the following growth experts collaborated to share their views on low-code building tools for AI agents, vertical-specific applications, and other enabling technologies:
- Nishchal Khorana — Associate Partner, Managing Director, and Growth Coach, ICT at Frost & Sullivan
- Prem Balasubramanian – CTO and Head of AI at Hitachi Digital Services
- Bernardin Arnason — Growth Expert and Industry Director, ICT at Frost & Sullivan
- Kiran Kumar – Growth Expert and Director, ICT at Frost & Sullivan
Actionable Insights from This Webinar
- What Sets Agentic AI Apart from Traditional Systems
Agentic AI represents a huge leap forward from traditional AI systems to autonomous, goal-oriented technologies that are capable of planning, executing, and adapting themselves with minimal human input. Unlike generative AI (GenAI) and large language models (LLMs), which respond to prompts, agentic systems proactively initiate tasks, set goals, collaborate with other AI agents, and manage multi-step workflows with the help of memory feedback loops and continuous learning. This has the potential to enable automation of higher-order tasks, moving beyond simple productivity gains to intelligent, end-to-end workflow automation.
- Growth Drives Pushing Enterprises to Adopt Agentic Systems
Enterprises adoption is linked to four key drivers. First, the ability to autonomously perceive, reason, and act in complex environments — addressing challenges that go beyond rule-based automation. Second, expanding multimodal capabilities (e.g., interpreting images, video, and voice) that enable broader use cases, especially in complex industrial settings. Third, demonstrating measurable business value by improving efficiency, accuracy, and cost reduction across workflows (e.g., invoice processing). Lastly, focusing on trustworthy, responsible AI frameworks to build confidence for enterprise-scale adoption.
Which growth processes will help your teams scale infrastructure to maximize AI readiness in your organization?
- Emerging Growth Opportunities and Business Applications
Agentic systems are driving real-world impact across several business functions:
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- In the near term, enterprises are adopting AI agents for process automation, where agents streamline repetitive workflows across enterprise resource planning (ERP), customer relationship management (CRM), and IT service management (ITSM) interfaces.
- Customer service is another hotspot, with intelligent agents enhancing customer engagement through conversational AI, virtual agents, and self-service capabilities.
- In banking and financial services, autonomous agents are being used to monitor transaction patterns (flagging, approving, or investigating activities) to reduce fraud.
- In the medium term, predictive maintenance and guided repair have the potential to become mainstream, where agents use multimodal inputs to anticipate failures and assist in complex repairs across manufacturing environments, thereby minimizing downtime. This means that hands-free, voice interactions with drones can offer better control in hard-to-access, industrial environments.
- In the long term, AI agents can simplify the deployment of custom models and commoditize traditional AI. This translates into shorter timelines for model training and automated data lifecycle management.
- Thwarting Challenges and Strategic Imperatives in AI
The top barriers to AI and GenAI adoption remain data privacy, security, and governance concerns; difficulty in measuring (and improving) return on investment (ROI); and the widening gap in necessary skill sets. These challenges are even more pronounced with Agentic AI, where autonomous decision-making raises the stakes for governance and oversight. Measuring value becomes harder as benefits are indirect and long-term, while talent needs expansion with respect to multi-agent systems and domain-specific expertise.
In conclusion, Agentic AI is redefining industries, creating new growth avenues. But success hinges on strategic integration, trusted ecosystems, and skilled talent. Organizations that act now can lead the shift toward intelligent, autonomous operations. The question is — How will you identify the most lucrative AI opportunities for your business?
Click Here to connect with Frost & Sullivan’s AI and data analytics growth experts for customized opportunities, tech strategies, and best practices in agentic AI!
“With Agentic AI, we are moving from assistance to autonomy, enabling AI to not just assist, but to take decisions based on judgement and lead actions towards concrete business goals.” – Kiran Kumar, Growth Expert and Director, ICT at Frost & Sullivan.
