_{The Evolution Toward Agentic AI}

_{The evolution from GenAI to Agentic AI is marking a natural progression in artificial intelligence development.}

While GenAI has captured public attention due to its ability to create convincing and sophisticated content, the evolutionary next phase of AI is the move toward systems that do more than just generate – systems that are capable of multiple orchestrated actions.

This shift is on the cusp of application as some organisations are already moving beyond AI powered chatbots toward fully autonomous AI agents capable of executing real world decisions. Advances in reinforcement learning, self-improving algorithms, and AI autonomy are making it possible for AI to operate with less human supervision, further reducing reliance on manual decision making.

Hybrid models are also set to emerge, where GenAI provides insights, and Agentic AI acts on those insights. In financial services for example, existing GenAI models can produce investment reports analysing market trends in the context of a portfolio, but an Agentic AI system would be able to autonomously adjust that portfolio based on those insights, executing trades and optimising risk exposure without human intervention.

Hybrid models are also set to emerge, where GenAI provides insights, and Agentic AI acts on those insights

This convergence and merging of the capabilities of GenAI and Agentic AI will shape the future of automation, redefining the role of AI in industries that rely on precision, speed, mass customisation and intelligence driven decision making.

As artificial intelligence continues to evolve, it is crucial to plan your business goals through recognising the fundamental differences between GenAI and Agentic AI. While GenAI enhances productivity through content generation, Agentic AI pushes the boundaries of autonomy, executing decisions and achieving

complex goals, potentially entirely without human oversight.

For businesses and industries adopting AI, understanding this distinction is critical for aligning AI capabilities with strategic objectives. GenAI will remain a powerful tool for assisting with creative and analytical tasks, but the real transformation lies in Agentic AI’s ability to take independent action, drive automation, and make intelligent decisions at scale.

The future of AI is not just about enhancing human workflows—it is about redefining them entirely. As Agentic AI becomes more prevalent, businesses must prepare for a new era where AI does not just support decisions but actively makes them, ushering in a future of intelligent automation and unprecedented efficiency.

The rise of the “Do It For Me”, DIFM economy

The way individuals and businesses interact with products and services has undergone a profound transformation, driven by changing consumer expectations and rapid technological advancements. This evolutionary development is set to continue, and it too will evolve.

We are transitioning from the world of “Do It With Me” to “Do It For Me”, at an astonishing pace.

Increasingly, people are wanting to move away from carrying out repetitious tasks for themselves which they had to perform simply because there was no alternative. Instead, there is now a surge of recognition born from GenAI that low level tasks can be handled by these tools.

Modern users, accustomed to seamless digital experiences, increasingly expect frictionless interactions where technology removes the burden of manual effort.

Agentic AI is going to take this to an entirely new level. We are now headed rapidly toward the DIFM economy. This shift is fuelled by the growing capabilities of automation and AI driven decision making, and will dramatically increase with the growth of Agentic AI systems that require little to no human intervention.

Consumers will no longer just want tools that help them accomplish tasks; they will soon embrace and then expect intelligent systems to anticipate their needs, take action, and deliver outcomes seamlessly.

The DIFM economy optimises for efficiency, accuracy, and personalisation, allowing users to delegate responsibilities while technology handles the execution.

The transition toward DIFM will be driven by this Agentic AI technological evolution, moving from

manual control to assisted intelligence, and then into autonomous execution. In the past, users took full responsibility for completing tasks, even if they had access to tools that facilitated parts of the process.

As automation technology becomes more sophisticated, industries can move toward an ecosystem where consumers and businesses rely on intelligent agents to handle responsibilities proactively and autonomously.

The demand for speed, efficiency, and personalised services will push businesses to develop AI driven solutions that minimise the need for active user involvement. Another significant driver in this evolution is the explosion of real-time data availability.

AI systems thrive on data, and the proliferation of connected devices, IoT sensors, and real-time analytics has allowed AI driven platforms to make more context-aware, hyper-personalised decisions. This enables financial services, healthcare, and even home automation to function more intelligently and independently.

For businesses, the drive for efficiency and cost reduction makes the desire for DIFM an attractive model. Automated systems can reduce operational costs, minimise errors, and free up human resources for higher-value activities.

“Automated systems can reduce operational costs, minimise errors, and free up human resources for higher-value activities”

Enterprises are rapidly adopting AI driven workflow automation, customer support, and financial management to improve productivity and enhance service delivery at scale. Finally, the maturation of AI agents has allowed for proactive task management across multiple domains. AI powered systems will largely move beyond being reactive assistants - they shall analyse context, anticipate needs, and independently complete tasks across finance, business operations, healthcare, and smart home automation.

The question is no longer whether AI will take on more responsibilities - it’s how businesses and individuals will adapt to a world where AI doesn’t just help but does it all.

The DIFM Economy in Action: Real-World Applications

DIFM is already starting to reshape multiple industries, replacing manual decision making with AI driven automation. In personal finance and wealth

management, robo-advisors have pioneered the concept of AI managed investment portfolios.

Commercial Agentic AI platforms can autonomously construct, rebalance, and optimise portfolios, making investment management a hands-free experience for users. AI driven financial assistants now categorise transactions, optimise spending, and even negotiate bills without requiring direct user intervention.

We are seeing these tools emerge in our day to day lives in the form of the smart home industry with AI driven devices optimising everyday life. Systems like Nest thermostats automatically adjust temperature settings based on learned behaviour, virtual assistants like Siri and Alexa handle scheduling and smart device coordination, and automated replenishment services ensure household supplies are restocked without manual ordering.

In business operations, AI powered customer support agents are reducing the need for human interaction by autonomously managing inquiries and resolving customer issues in real time. Workflow automation tools are streamlining business processes such as supply chain management, procurement, and contract execution, enabling companies to run more efficiently without human intervention.

AI driven marketing platforms, like those used by Meta and Google, continuously optimise advertising campaigns, adjusting targeting and spend without requiring constant human oversight. In healthcare and personal well-being, AI powered wearables now track vital health metrics, offering proactive health insights and early warnings for potential medical issues.

“AI driven marketing platforms, like those used by Meta and Google, continuously optimise advertising campaigns, adjusting targeting and spend without requiring constant human oversight”

Prescription management systems remind patients about medication schedules and automatically request refills when needed. AI driven platforms analyse patient symptoms and behavioral patterns to provide personalised health recommendations without requiring frequent doctor visits.

The trajectory of DIFM and Agentic AI suggests that AI powered automation will become even more deeply integrated into daily life. Personal AI agents will coordinate everything from finances to healthcare and logistics, reducing the need for manual engagement. Autonomous professional services, including AI driven legal, medical, and financial advisory services, will begin to replace traditional human-led processes, providing instant, scalable, and efficient solutions. Rather than eliminating human involvement altogether, the future of DIFM will likely involve a new model of human-AI collaboration.

“Agentic AI powered professional services will be instant, scalable and efficient, involving a new model of human-AI collaboration”

Users will shift from active participation to strategic oversight, where AI systems handle execution, while individuals intervene only when necessary.

The success of DIFM will depend on finding the right balance - leveraging AI for efficiency while maintaining human agency, trust, and control.

“The success of DIFM will depend on leveraging AI for efficiency while maintaining human agency, trust, and control”

These ever growing examples illustrate how DIFM is moving beyond simple automation to create a world where AI takes responsibility for tasks, adapts to user needs, and independently optimises outcomes.

The application of Agentic AI to drive DIFM outcomes are very extensive indeed.