Agentic AI has been all over the news recently with announcements from established players like Google (Agentspace), Amazon (AWS Nova Act), and PwC ("Agent OS" platform) and startups like Unsupervised and Crew AI. This emerging technology has the potential to redefine the way businesses and even individuals interact with the digital and physical world.
But for civilians still refining their ChatGPT prompting skills (no judgement), what exactly is agentic AI? More importantly, how can businesses leverage a multi-agent platform like Google Agentspace with App Orchid’s semantic layer and data and analytics agentic capabilities? For decision makers preparing for what’s next, here’s everything you need to know.
The name’s AI, Agentic AI: Making work simpler and easier
AI agents are autonomous systems that complete tasks and act within digital and physical worlds on behalf of the user. They use AI models to understand the user’s ask, use reasoning to break it down into smaller manageable steps and execute those steps autonomously.
If this reminds you of robotic process automation (RPA), you’re not off base. AI Agents are a quantum leap forward. Instead of rigid, repetitive behavior from RPA bots, AI Agents understand the environments and can adapt to changing circumstances, calling upon a repository of tools to accomplish the task.
These agents can integrate multiple AI models, use tools available to them, and make complex, multi-step decisions— like a digital assistant that actively works on your behalf rather than just responding to your requests with text.
.png)
Today, most agentic tools enable us to solve simple tasks. For example, I asked an agent to help me prepare for a meeting as a test of an agentic platform this afternoon. It prepared a brief with of the company with:
- Recent news and investments
- Recent investor call summaries and key highlights
- Bios of the meeting attendees,
- Summaries our past discussions from emails, etc.
This task would have taken me an hour or two fore AI, it now took just minutes. As AI agents mature, they will grow in complexity to solve very high-level problems, like planning a vacation or organizing a company retreat.
For the average business, agentic AI will unlock new growth opportunities. Small and mid-sized businesses will be able to compete with larger players by leveraging automation and intelligence in ways that were previously only accessible to global enterprises.
The world is your itinerary
Agents will also fundamentally change the way people use common tools. I attended a workshop last week where attendees were asked what one work-related task they wish Agents would solve for them. Over half, including me,responded with “Travel Planning and Expenses Management.”
.png)
Planning travel can be a hassle, with multiple tools for flights, hotels, rides, meals, rental cars and activities. Some AI-powered travel sites suggest options, but manual decisions still dominate tasks like booking flights or hotels. Plus, coordinating a single seamless experience requires multiple tools and apps.
Agentic AI introduces autonomous information gathering, decision-making, and personalization based on your previous vacations. It can create a rich itinerary across many sites and present it to you for approval. And this doesn’t have to stop once you plan the trip. In the future, agents will continuously manage your trip—flight delays, local events, weather, emerging discounts—and automatically adjust plans to make the most of your time and budget.
In other words, agentic AI acts like a digital concierge that not only plans but also anticipates your needs, adjusts on the fly, and manages every aspect of your trip with little to no input from you. It’s the evolution of convenience, offering not just a travel itinerary but a fully realized, autonomous trip planning experience.
The promise of Google Assistant, Siri and Cortana may finally be realized.
Agent experience design
This agentic experience brings new challenges to companies. Companies like Expedia, Kayak and Viator will need to drastically reimagine how they operate in the agentic era. Suddenly there’s a need to design apps that operate with agents seamlessly. Agents don’t sleep - they can wake up at 4 am to find the best prices for flight tickets. Design cues (“Room availability is almost gone!“) that work for humans will no longer be as effective for making a sale.
When Apple released the iPhone, technology companies scrambled to change web and app design paradigms for smartphone displays. The same will be true for agentic AI. Product design will need to be based on making solutions easy for agents to use. We call this agent experience design and it will be just as important as user experience design. Companies will need agents to use their tools without disruption. Stripped down experiences, seamless data sharing, new structures for metadata and context and speed to answers will be important. What seems obvious for human-centric design will need to be updated for agents.
Enterprises will need to reimagine their internal operations because they will be threatened by nimble companies punching above their weight enabled by agents. Imagine, what if you could orchestrate multiple agents to solve complex tasks at scale?
Imagine a customer retention marketing use case. A sales manager wants to target customers near the end of their contract with a renewal discount. So she provides a series of instructions, “Create an offer for customers near the end of their contract who have not renewed. Restrict the offer to European customers in countries where our competitor’s market share increased in the last year. Offer them two months of service discounted by 25%.”
When given a task, agents can clarify instructions and execute work instantly working in tandem:
- A customer data agent compiles the list of customers near contract’s end.
- A research agent identifies countries where competitors are gaining market share.
- An email agent writes the offer with personalized details.
- An image generation agent creates graphics customized to the customer and locale.
- A contract agent writes contract terms with the offer.
- A calculator agent converts any financials into local currencies.
- A translation agent formats emails in local languages.
The agents can be orchestrated automatically. An approval process can bring all this work together for the people who ask for it. What previously required tedious coordination and days of effort is now accomplished seamlessly in minutes.
Final thoughts
The rise of Agentic AI represents one of the most exciting transformations in business today. To harness the potential of agentic AI, businesses need to align their strategies with this paradigm shift. This includes fostering a culture of innovation, adopting agent-friendly design principles, and leveraging multi-agent platforms in combination with App Orchid’s Easy Answers to thrive.
App Orchid is working with major agentic platforms to incorporate our technology. For example:
- Easy Answers™ can be embedded as a data and analytics agent in a multi agent process.
- Agentic platforms will need a semantic layer that understands and works with structured database data - a core capability of App Orchid’s unique context-enriched knowledge graph.
- Getting data ready for agents will be paramount - App Orchid can act as the middleware for your data and AI models with the ability to pre-process data from many sources for agentic access.
Are you ready to start exploring what’s possible—from building agentic workflows to cutting-edge insights? Schedule a consultation with App Orchid today to explore how agentic AI can transform your business.