Is AI fluency the ingredient or the result of an AI-ready workforce?

Organizations are racing to adopt AI, pursuing real-world use cases to drive new growth, boost efficiency and productivity, and sharpen their competitive edge. But even as AI roadmaps speed up, a crucial truth is emerging: The latest technologies and tools will be wasted if you don’t bring your people along for the journey. 

The arrival of the AI era signals a foundational shift that redefines how work gets done, impacting everything from daily tasks to processes to job roles. While early initiatives are already delivering tangible gains, most organizations are quickly realizing that they need much more than a simple technology upgrade to realize AI’s full potential. They also need AI fluency — the ability to effectively, ethically, and confidently use AI to amplify individual and business performance.We consistently find that the organizations achieving the highest levels of success are those that are ready to effectively use AI. They are proactively taking steps to future proof their workforce, helping employees to understand where AI fits into their roles, how it can enhance their work, and ways they can collaborate with it to drive innovation. 

Our experiences guiding customers through this transition have highlighted four critical areas for consideration to achieve an AI-fluent organization. By prioritizing these key workforce changes and aligning them to your AI strategy, you can ensure your talent is prepared to capture the full transformational value of AI. 

1. Organizational design

AI is poised to bring huge changes, both subtle and sweeping, that will transform every role and business process across the enterprise. Going forward, we believe that organizations will need to redesign for a hybrid workforce, where humans and AI collaborate together to get work done. 

What’s really driving this next phase is the rise of AI agents — systems that combine advanced AI models with access to enterprise tools and data to take actions on the behalf of users, under supervision — creating opportunities to augment, automate, transform, or even delete existing ways of working. These advancements mean we need to rethink organizational structure, business processes, workflows, and governance, sometimes from the ground up. 

A good place to start is mapping out AI’s impact on specific roles, thinking about how AI can reduce frustration and free up time for more valuable, fulfilling work. For example, within retail, routine customer service queries like order tracking or basic inventory checks can largely be automated and taken over by AI agents. AI could also augment marketing efforts by analyzing customer purchase history and generating personalized recommendations based on individual preferences. In other cases, responsibilities might completely transform — instead of manually gathering data and compiling reports, for instance, a financial analyst might now focus more on strategic scenario planning, advanced risk modeling, and complex decision support. 

Looking at how AI impacts different roles not only helps reveal existing friction within your current business processes but provides an opportunity to create better workflows that address these issues. For instance, one of our large global professional services customers is using AI to reimagine core back-office processes like order processing, supply chain, and human capital scheduling instead of integrating it into already established workflows. In a similar vein, a leading multinational retailer has built a human-plus-AI workflow that provides employees with agentic assistance to improve product-to-market and merchandising activities. 

2. Employee profile evolution

Cultivating a workforce with an AI mindset is another important step towards building an AI-ready workforce. As AI increasingly becomes capable of managing tasks that require specialized knowledge or technical skills, organizations need to focus on developing employees with broader knowledge. You need people who are not only naturally curious to continuously learn but also comfortable with adapting to the fast pace of AI technology. Beyond hiring on fresh talent who already have the skills and are eager to use various types of AI, companies should invest in upskilling and reskilling their existing workforce by offering both organization-wide learning programs and targeted training for specific roles and functions. What we’ve learned from our research is that employees benefit most from hands-on practice with real-world scenarios and flexible, accessible learning resources that can be customized to fit individual learning styles, skill levels, roles, and organizational needs. 

Within Google, we have adopted a continuous approach to learning for both Googlers and our customers. Learning is truly part of our culture and embedded into our daily workflows. We share a constant feed of information with Googlers, from tips and trips to shared best practices in town halls. In addition, we incorporate more experiential, collaborative learning, such as hackathons, to create opportunities for people to play with AI concepts, fail fast, and learn from each other. 

We also recently announced Google Skills — our new learning platform, which offers the best of AI from across Google, consolidating over 3,000 courses and labs from Google Cloud, DeepMind, and Google for Education. Learners can select the skills and tools they need to build a customized learning journey of the most relevant content in our vast catalog, allowing them to easily build their AI skills at their own pace and on their own schedule. 

3. Tool enablement

As AI takes on a larger role in both our personal and professional lives, employees will face a growing disconnect between the AI tools they use outside of work and those provided on the job. In fact, some research suggests that “shadow” generative AI usage has surged by 68% in modern enterprises, highlighting a growing trend of employees using unsanctioned tools to complete their tasks, often without realizing the security implications. This widening gap shows how critical it will be to offer employees vetted, secure AI tools they can use to safely explore and experiment with AI. 

For organizations, the main priority is paving the way for adopting AI tools that can make day-to-day work experiences better, all while ensuring AI governance, security guardrails, and responsible AI practices. If you don’t give curious and motivated employees approved tools they can use with direct company oversight, they’re just going to use whatever they can find. That, in turn, is likely to put your organization at high risk of security, data, and policy breaches.

To make smarter choices,  the entire workforce — from C-suite to entry-level — need a practical understanding of responsible AI use to learn how to safeguard sensitive data, verify AI responses for accuracy, and steer clear of ethical issues. Transparency and open communication around how new tools are selected, implemented, and governed is also critical for introducing new capabilities safely without compromising corporate and ethical standards. Adopting AI platforms is another way to simplify this process, enabling easier paths to access, develop, and manage AI models, agents, and applications at scale. 

Gemini Enterprise, for example, brings the best of Google AI to every employee through an intuitive chat interface, serving as a single front door for AI in the workplace. Powered by Google’s most advanced Gemini models, Gemini Enterprise securely connects enterprise data with a no-code workbench, and a taskforce of pre-built Google agents, custom agents, or other agents from our extensive partner ecosystem. Organizations can visualize, secure, and audit all their agents in one place, allowing them to move beyond simple tasks to automating entire workflows.

4. Human experience and culture

The final, and arguably, most crucial, consideration when establishing AI fluency is building the right culture for AI to thrive. Put simply: No workforce changes will matter if AI isn’t first grounded in a culture of trust and psychological safety.

Currently, many organizations still lack an AI-positive culture, leading employees to hide their use of AI or hesitate to engage with it due to uncertainty about whether they can use it or fear of making a high-stakes error.  I've personally observed how a culture lacking in psychological safety can deter employees from experimentation, risk taking and growing comfortable with the onset of AI tools.

To overcome these challenges, we have found it helpful to frame AI workforce transformation against the human experience, emphasizing the shift from repetitive tasks to higher value work that is more fulfilling, less frustrating, and more impactful. Employees are co-designers of this new AI-powered operating model, so it’s important to provide opportunities for employee-led creativity and company-wide recognition. 

At the same time, we believe that nothing shifts culture faster than when leaders promote and openly share their own imperfect experiments with AI — their most useful prompts, the lessons they’ve learned, and the tasks they're still learning how to delegate. This helps foster an environment where employees can voice concerns, ask questions, and experiment without feeling judged or being afraid to fail. Leaders from every level of the organization should actively champion the exploration of AI and celebrate experimentation within their teams and across the organization. 

Looking ahead

AI fluency isn’t a finish line, but a continuous commitment to cultivate a workforce that is primed to work with and alongside AI into the future — and we’ve already seen proof of its impact. 

Our 2025 ROI of AI report found that early adopters of agentic AI — the companies we see prioritizing organizational fluency — are seeing significantly greater returns from their AI investments. These leaders are not only allocating 50% or more of their future AI budget towards AI agents but also working to deeply integrate them across their operations. The sheer scale of adoption is a testament of the success these efforts can bring: Nearly 40% of all executives surveyed reported their organizations have already launched ten or more agents. This rapid progress and momentum provides clear evidence that organizational AI fluency is a powerful driver of AI value. 

Ultimately, the enterprise in the AI era will look fundamentally different, defined not just by technology but also the collective capability of the people using it. This means that building AI fluency within your own organization isn’t just another training initiative — it’s a definitive business capability that can help you capture the full transformational value of AI.