5 insights to build your agentic AI advantage in 2026

If your current AI strategy is still centered on building chatbots to answer questions, you might be overlooking one of the biggest AI opportunities of all: AI agents. 

Agentic AI is quickly moving AI from a tool to a collaborative partner, with the potential to reshape every industry, job, and task. Our 2026 AI Agent Trends report confirms agents are set to redefine productivity, automate core business processes, deliver hyper-personalized experiences, and supercharge security, while emphasizing the need to prioritize building an AI-ready workforce. 

But the biggest takeaway for leaders is this: If you’re not seriously engaged in exploring AI agents, you’re putting your organization at a competitive disadvantage. 

To help you translate these trends into a winning strategy, I wanted to share five key insights around what’s working now and what’s coming next that can help guide your AI agendas for the coming year. 

1. Build AI agent muscle today for more value tomorrow. 

With their ability to independently reason, plan, and take secure actions to achieve specific goals under human supervision, agents provide incredible opportunities to speed up work and drive greater efficiencies. The first battleground for gaining early momentum will be internal, line-of-business functions, such as financial planning and accounting, procurement, contract management, legal, and HR. 

AI agents excel at repetitive tasks, making them ideal for streamlining mundane, manual workflows. Within enterprise operations, agents can help automate complex data aggregation, simplify compliance, summarize and extract information from documents, generate standardized materials or content, and provide instant answers to internal policy questions. For instance, an agent could help a portfolio manager summarize revenue and earnings for the past five years or take over drafting compliance documentation for a pharmaceutical scientist, giving them more time to focus on high-impact, high-value work and increase their productivity. 

In addition, agentic capabilities also promise to fundamentally redefine business processes that center on creativity, execution, repetition, and communication. Marketing use cases for agentic AI, in particular, are growing fast, driven by the immediate cost savings that can be achieved through more efficient marketing operations and the ability to deliver more targeted, personalized campaigns. More crucially, these early efforts are helping organizations build their agentic AI muscle. Internal business functions are the perfect foundation — the “low-hanging fruit” — for leaders seeking a lower-risk entry point for gaining deployment experience and getting their teams comfortable with AI. These use cases purely focus on improving internal efficiency and productivity, making them easier and faster to implement as they don’t directly impact customer interactions or products.

2. Take automation to new heights with next-gen workflows.

With advancements like the Agent2Agent (A2A) Protocol and the Agent Payments Protocol (AP2) making it easier to connect agents to each other and enterprise systems, the next level of intelligence will be multi-agent systems, where multiple agents will work together and communicate to orchestrate and execute tasks — even if they are from different developers, built on different frameworks, or owned by different organizations. 

While companies will focus on increasing internal efficiency and productivity first, the longer-term transformative potential will be automating multi-step workflows across platforms, teams, and even value chains. This interoperability could enable manufacturers to authenticate that supplier requests reflect their true intent and establish a clear audit trail for accountability in the event of a fraudulent transaction or fulfillment issues. Or, a maintenance lead could use an agent to mitigate production delays caused by out-of-stock spare parts, monitoring for risks across an entire supplier network and executing an entire contingency plan — including conditional procurement and sourcing — while adhering to predefined financial or logistical constraints. 

3. Capture competitive edge with more helpful experiences.

For the last decade, customer service automation meant pre-programmed chatbots answering simple questions and deflecting support tickets. While they were efficient and useful, they lacked the ability to understand more nuanced and complex questions. 

Now, with new developments in AI models and open protocols like A2A, agents are enabling “concierge-style” experiences, especially in the retail industry. AI agents can connect enterprises and customers by remembering preferences and past conversations to offer human-like interactions and guidance to deliver truly one-to-one experiences.

One shining example is the emergence of agentic commerce, where agents are handling the entire shopping journey: packaging up recommended items based on context, negotiating with merchants and other agents for price, stock, and delivery, and eventually even executing transactions on the customer’s behalf.

Initially, this will be delegating routine shopping tasks — a consumer will share “I need to replace this athletic shirt,” and an agent will find the best price in the color desired and purchase it. However, the ultimate future vision is total orchestration, where agents can be trusted with complex, multi-variable tasks — such as planning a trip to Norway in February — identifying all the necessary gear based on travel dates, negotiating prices based on budget, and determining the best combination based on vendors, inventory ability, and shipping methods. 

These capabilities also have wider implications for scenarios such as helping consumer packaged goods companies build direct-to-consumer relationships and gain first-party data, and within the travel and hospitality space, solving the deeply painful process of manually researching and booking every single element of a trip.

4. Prioritize trust to support widespread adoption.

Agentic AI provides new paths to address the enterprise’s most common pain points, eliminating the chronic toil that slows teams down. In modern security operations, for instance, AI agents can process massive amounts of data faster than any human to automate draining security responsibilities like alert triage. This capability combined with advanced multimodal reasoning is what allows agents to make faster, better decisions, all within pre-defined parameters and rules.

Yet, despite these advantages, organizations face a significant hurdle before they can achieve adoption at scale: Trust.

For people to embrace AI agents, they need to have confidence they can delegate to them and trust what is generated and delivered. The stakes here are substantial as the risk of misuse and a lack of authenticity can lead to significant brand backlash, especially if employees fail to fully understand the potential security risks.

Agents don’t arrive magically ready to do everything; they require important groundwork to ensure they can function and execute their tasks safely and reliably. Businesses should be the stewards of trust by ensuring the tools and technologies they choose also enable them to meet security, privacy, and governance requirements. For example, Gemini Enterprise brings the best of Google AI into a centralized, enterprise-ready platform to build, run, and govern AI agents responsibly and securely connect them with enterprise data wherever it lives. 

5. Put people (not prompts) at the heart of your AI initiatives.

The AI era will place a new premium on valuable human skills like critical thinking, problem-solving, and genuine human connection as agents automate more repetitive work. 

Think of it this way: the traditional career pyramid is flattening into a diamond, pushing human talent towards more strategic roles. While core operational functions aren’t going anywhere, how that work gets done is fundamentally transforming — and organizations have to be proactive about reskilling and upskilling their existing workforce to prepare for this change. Ultimately, AI success will largely hinge on AI fluency, the ability to effectively, ethically, and confidently use AI to amplify individual and business performance. 

The immediate imperative is simple: Every employee, whether front-line worker or executive, will need to gain hands-on familiarity with AI tools and models. For organizations, the highest priority will be taking steps to establish a culture of innovation that encourages AI use without fear and developing adaptable, continuous learning plans that enable them to get practical experience at their own pace and on their own schedule. 

Looking ahead

We’re headed towards a profound shift that will fundamentally change how every business operates, competes, and creates value. This future is already being built, with advancements capable of generating new interactive worlds or building an AI-powered applications — with a single prompt. AI agents are the next frontier, driving radical efficiencies and productivity that allow every organization to do more, invest more, and engage more deeply with their market, redefining the operating economics and competitive dynamics across every industry.

Learn more about how AI agents are ushering in a new era of change in our 2026 trends reports for retail, manufacturing, financial services, telecommunications and healthcare & life sciences.