In just a few years Generative AI has completely changed how people approach their work – tools powered by large language models help us draft content, summarise information and carry out our everyday tasks faster than ever before.
As the AI evolution continues apace, the next phase of artificial intelligence is emerging…The focus is no longer around aiding users generating content and building efficiency – it’s shifting to how we harness AI to complete tasks and automate processes themselves.
That’s the difference between generative and agentic AI. One responds to prompts. The other works towards goals, taking real action across systems and processes. This is an significant shift into the next phase of AI, and is already shaping how organisations think about AI investment from here.
What is generative AI?
Generative AI focuses on creating content and information based on prompts. Powered by generative AI models and natural language processing, these tools can generate text, images, reports, and software code using large amounts of training data.
Many organisations already use generative tools for:
- content creation
- summarising documents or meetings
- analysing data
- supporting software development
BUT human input still matters
Whilst generative AI is powerful, it still relies on human direction and judgement. A user prompts the system, reviews the output, and decides what happens next.
That’s why generative AI works best assisting people, enabling users to work faster, and enhancing capability rather than replacing them and running entire processes.
Agentic AI – what’s different?
The key difference in agentic AI vs generative AI is how the technology operates. Generative AI focuses on producing content, whilst agentic AI systems work towards defined goals and take action.
Generative AI answers – Agentic AI gets things done.
AI agents plan actions, access external tools, and complete multi step tasks across multiple systems like humans.
For example, agentic AI can:
- gather real time data
- analyse data and identify patterns
- trigger actions in other AI systems
- complete workflows
Agentic AI works with minimal human input, while still allowing human oversight and human supervision like any human workforce.
This makes agentic systems well suited to workflow automation, complex tasks, and multi step processes, enabling those current resources to focus on adding business value elsewhere.
How is Microsoft is enabling the shift to agentic AI?
The shift from generative to agentic AI is becoming a major focus across the IT industry and through platforms like Microsoft Copilot and Power Platform, Microsoft is a the forefront, expanding AI capabilities to support AI agents and automate workflows to connect across business applications.
These AI powered solutions aim to move beyond simple content generation and enable agentic AI systems to manage parts of an entire process, including areas like automated workflow management, virtual assistants, and internal operations.
What this means for organisations right now
For organisations exploring agentic AI vs generative, the key point is that both technologies will work together.
Generative AI models help create information and support decision making.
Agentic systems focus on completing tasks and managing workflows.
Together, they can support:
- repetitive tasks and workflow automation
- analysing market trends or emerging threats
- internal AI applications and digital assistants
- operational areas like financial risk management
Even as AI technology evolves, human involvement remains essential. Agentic AI may operate with minimal human intervention, however human oversight is still critical for governance and decision making.
Conclusion
The difference between agentic AI vs generative AI is simple.
Generative AI focuses on creating information.
Agentic AI focuses on taking action and completing tasks.
As AI technology continues to evolve, organisations will increasingly combine both agentic AI systems and generative tools to build smarter AI solutions. The opportunity is not just better productivity. Agentic AI and generative AI together have the potential to genuinely transform how work gets done, delivering competitive advantage while often reducing cost.
If you’re exploring how AI could support your organisation, now is the time to start identifying the processes where AI could move beyond simply assisting work to actually completing it.