Our research shows an impatience to move fast with AI—85% worry they risk falling behind—but successful adoption is not as simple as turning a switch on technology. Here are the key considerations we recommend you prioritize now:

Your organization’s strategy is your AI strategy. While agents expand the possibilities of AI by acting autonomously, their goals and behaviors need to sit within the parameters of your strategy, values and principles—in the same way we expect of human employees. If your organization is one of the 30% still crafting a visionary AI strategy, we recommend you start here. This will give you a ‘north star’ to decide where to adopt technology, how to train your people and which tasks or processes agentic AI should handle.
Decide how much ‘agency’ agentic AI should have. Despite most using AI to make decisions, only 26% fully trust the results and just 39% have a complete set of responsible AI guidelines in place. This exposes an urgent need for leaders to agree the right level of risk tolerance for their organizations. If agents drive more workflows, and employees make fewer choices, how will you set thresholds for human intervention? With this will come the need to continuously train and fine tune AI agents so that they ‘forget’ and unlearn misguided or unethical facts.
Prioritize the human factor of AI adoption. With only 33% very confident that their leadership can reliably differentiate between AI and human-generated work, how will you measure the contributions of AI compared with human employees? The impact of what makes us human at work—our desire for belonging, engagement and purpose—should also not be underestimated. It’s clear we have work to do, as only 40% feel very confident in the ability of leaders to manage the social and emotional aspects of working with AI.
Data still matters for agentic AI. Copilots and agentic AI share the same data foundation—large language models (LLMs). A robust data strategy—which defines how data is collected, stored, managed, analyzed, and utilized—is essential for AI success. The combination of productionized tools, such as Microsoft Azure AI Foundry, with the security and governance rules and principles of platforms like Microsoft Purview, is an important piece of the puzzle. By securely bringing together data from multiple sources these tools will create a standardized architecture that can accelerate the time it takes to create and scale new agents.

To get more insights into AI value for 2025, and what this means for you, download our latest research Avanade Trendlines: AI Value Report 2025

Agentic AI: What to know now about the next big breakthrough