The Rise of Agentic AI

Written by David (DJ) Morimanno, Field CTO, North America at Xalient

1 December 2025

Is Agentic AI just a phrase doing the social media rounds? Is it important at all, and should we just consider it as part of the general AI approach we need to consider? Are there any pros/cons of new Native-AI enterprise IT tools versus legacy solutions with a good old fashioned AI Bolt-On.

First off, should we even care about Agentic AI?

• Personal use: Agentic AI could transform our lives even more than the internet. For instance, people are now buying cars in the US, using Agentic AI—feature research, service feedback, price comparison, dealership selection, and financing. With AI agents, it is a short step to even higher value activities, such as refinancing a house – replacing the traditional human broker.

• Changing nature of IT: IT are deploying some early types of AI agents, whether through simple chatbots for HR and internal service operations – or replacing more complex workflows in customer interactions. These changes are requiring increased investment and are causing massive changes to the enterprise software stack. As ever, new tech brings a change to cyber threats, demanding proactive mitigation.

• Careers: Traditional roles like coders and designers may become less relevant. With tools like ChatGPT Plus, tasks such as data visualisation are now handled quickly through natural language prompts. Therefore, the question is: what skills should we focus on for our own personal development (and the next generation)?

In a similar way to the last decade where the “Cloud first” strategy cry was heard everywhere, a new “Agentic AI first” call will now bellow across the IT landscape. In fact, investors are looking to support the rise of Agentic only companies taking on traditional
organisations – imagine a law firm, made up of a single lawyer and a team of legal Agentic AI – providing services to large institutions.

Background and Context

Most organizations build their IT stack around web presence, office systems, communication, finance, and HR — which often evolve into Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), service operations, and of course software development. Major suppliers of these systems create complex ecosystems that make switching difficult; requiring new connectors, workflow adaptations to support supply chain changes, or constant customization to respond to ever-evolving client requirements.

An estimated 5.7 million people work in the India IT Business Process Management sector, with hundreds of thousands dedicated to large players such as SAP, Salesforce, Oracle, and others — but with the rise of AI, most of these roles are set to become redundant.

Native-AI vs Bolt-On-AI

If you examine any of the tradition systems, software vendors are quickly attempting to add AI to their solutions. For example, in the CRM space, vendors have entered late and require extensive AI customisation which come at a high cost (e.g., the full suite of Salesforce Einstein AI is eye wateringly expensive). However, new kids on the block, such as Native-AI CRMs, like Aurasell and Creatio, offer radical changes such as the removal of writing complex workflows, combined with a more natural language interface – which is very compelling to those using a more pedestrian database front end. However, enterprises are cautious about adopting new foundational AI products, worried about introducing new business risks and rapid vendor changes.

However, perhaps the real question may be: why maintain enterprise stacks at all, if Agentic AI could eventually handle everything?

Imagining the Future

Key Agentic AI Categories

  1. Personal Assistant Agents: Microsoft Copilot exemplifies agentic help, integrated across Microsoft 365 for content generation, meeting summaries, document drafting, and more. Google’s Astra is another, offering multimodal capabilities akin to a Star Trek computer.

  2. AI Agents for Writing Code: GitHub Copilot, Tabnine, Codeium (Qodo), and Replit are getting so good now that applications can be written through a simple prompt in natural language. Satya Nadella, Microsoft CEO, notes that 20–30% of all code is already written by AI (10:30 into this video), a figure he believes will rise.

  3. AI Agents for Website Design: Tools like Tars Web Builder, 10Web, and Wix ADI create professional websites from simple prompts, handling Search Engine Optimization (SEO), imagery, and content. It is easy to predict that Agentic Engine Optimization (AEO) will become a new buzz phrase.

  4. Workflow Automation Agents: Zapier and Microsoft Power Automate connect apps, automate workflows, and provide enterprise-level process automation.

  5. Research & Analysis Agents: Perplexity and OpenAI’s Operator deliver concise, cited answers for complex queries, combining retrieval-augmented generation and advanced context management.

  6. Customer Service Agents: Ada and Sierra use natural language understanding and sentiment analysis to provide efficient, always-on support, handling everything from FAQs to escalations.

  7. Sales and Marketing Agents: Artisan AI automates lead qualification, pipeline management, and campaign optimization, leveraging behavioral analytics and CRM integration.

  8. Data Analysis Agents: Tableau Pulse and Microsoft Fabric/Power BI Copilot enable conversational analytics, dynamic dashboards, and predictive insights via natural language queries. Many enterprises can do this now with Copilot—just ask it to visualize a file for you, and in less than a minute you have an interactive web report.

  9. Creative & Content Agents: Copilot has a podcast generator that builds a 5–6-minute dialogue between a ‘virtual reporter’ and ‘virtual subject expert’ on any topic you prompt it with. Runway Gen-3 Alpha and Sora generate video and imagery from prompts. Check out the “Will Smith Eating Spaghetti Test,” and you can see how far this video creation has come in two short years.

  10. Specialized Domain Agents: Legal agents for advice and content support; DevOps agents automate deployment; healthcare agents analyze scans and manage records; finance agents detect fraud and optimize investments; education agents create adaptive learning paths and grade assessments. Some agents even manage teams of other agents.

Conclusion: Go proactive on Agentic AI planning as soon as you can 

Agentic AI is already reshaping how we work and create, making our digital lives smarter and more efficient. Whether automating tasks, generating content, or producing entire podcasts, these agents bring autonomy and specialisation. Any enterprise who wishes to stay ahead of the competition must have an Agentic AI strategy.

Picture of David (DJ) Morimanno, Field CTO, North America at Xalient

David (DJ) Morimanno, Field CTO, North America at Xalient

DJ helps clients develop IAM strategies that work in complex organisations. He’s an active practitioner and strategist, with nearly 20 years of hands-on experience in implementing market-leading IAM technologies across IGA, PAM, and Access Management. He specialises in building IAM Programs, administering IAM tools, and developing long-term strategies to support organisational objectives and business enablement. 

DJ has a passion for cybersecurity.  He is a trusted advisor for Fortune 500 clients and has helped industry executives successfully execute large-scale IAM programs through deployment.  He has extensive experience in financial services, energy, education, manufacturing, and healthcare industries. 

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