To be AI‑fluent is to understand AI, interact with it productively, and apply it to real problems at work; that capability is quickly turning into table stakes across industries.
As companies integrate AI into daily workflows, knowing how fluent your workforce is with AI can spell the difference between transformative productivity gains and missed opportunities. This article explains why you need to measure AI fluency, suggests courses to boost your team’s AI literacy, and shows how to measure AI fluency with Worklytics for data-driven insights.
Why You Need to Measure It
Tracking your organization’s AI fluency isn’t just a vanity exercise – it’s essential for continuous improvement and strategic alignment. Leaders increasingly recognize that simply rolling out AI tools isn’t enough; you must monitor how widely and effectively those tools are used to ensure they deliver real value. In fact, the old adage “you can’t improve what you don’t measure” rings especially true for AI adoption. Here are key reasons why measuring AI fluency is so important:
Drive Improvement and ROI: By measuring AI usage and proficiency, you create a feedback loop for improvement. It becomes possible to quantify theimpact of AI on productivity and outcomes – for example, how much time a new AI assistant is saving, which helps justify your AI investments. Tracking adoption and results is key to ensuring return on investment (ROI) from AI initiatives. If data shows an AI tool is shaving 10% off project times, you can double down on it; if not, you can refine your approach.
Identify Gaps and Guide Training: Measurement illuminates who is (and isn’t) using AI. Usage metrics can reveal pockets of high adoption as well as teams or departments that are lagging behind. If one department is barely touching the new AI tool, you can intervene with targeted training or support. Conversely, if another team has become power users and is saving hours with AI, you can spotlight their success and share those best practices across the organization. In short, data lets you focus your enablement efforts where they’re needed most.
Ensure Competitiveness: In 2024,75% of surveyed workers were already using AI at work – a figure that has likely grown even further. AI fluency is quickly becoming a baseline skill. Organizations that fail to measure and foster it risk falling behind more data-driven competitors. By benchmarking your AI adoption against industry peers, you can gauge whether you’re leading or lagging the pack and act accordingly.
Strategic Decision-Making: Measuring AI fluency provides executives with hard data to shape strategy. For example, understanding which tools deliver the most value or which teams struggle can inform decisions about where to deploy AI next or what training to invest in. It turns AI adoption from a vague ambition into a clear, data-driven discipline. In other words,visibility into AI usage helps align AI initiatives with business goals and course-correct early if needed.
In summary, measuring AI fluency in your organization ensures that AI adoption isn’t happening in the dark. It makes success measurable and challenges visible. With solid metrics, you can celebrate wins (backed by numbers), address weaknesses with concrete action, and continually refine how your people and AI work together.
Courses Recommended to Build AI Fluency
Improving your team’s AI fluency starts with education. Fortunately, there are numerous high-quality courses and learning paths – many of which are online and self-paced – to help employees at all levels become more AI literate. Here are some recommended courses (as highlighted by leading industry experts and search trends) to boost AI fluency across your organization:
AI for Everyone (DeepLearning.AI) – A popular introductory course taught by AI pioneer Andrew Ng. It’s beginner-friendly and non-technical, designed for people without coding backgrounds. AI for Everyone covers what AI can and cannot do, how to spot opportunities to apply AI in a business, and the broader implications of AI. This course provides managers and staff with a common foundation in key concepts, such as machine learning and neural networks, without requiring in-depth programming knowledge, enabling them to confidently participate in AI discussions and projects.
Elements of AI (University of Helsinki) – A free online course that aims to demystify AI for the broadest audience. Co-developed by academia and industry, Elements of AI starts from the very basics (no prerequisites required) and walks through foundational concepts, real-world applications, and the limitations of AI. Learners get a firm grasp of how AI works under the hood (in plain language) and what it can realistically do. This program has gained global recognition for training tens of thousands of people in AI fundamentals, making it an ideal solution for enhancing general AI literacy across an organization.
Microsoft Learn – AI Fluency Learning Path – Microsoft’s official learning path for AI Fluency is a collection of free, self-paced modules that provide a comprehensive understanding of AI from the ground up. It starts with the basics of AI and gradually progresses to more advanced topics, including generative AI and responsible AI practices. Notably, this path also introduces practical tools like Microsoft 365 Copilot and how AI features can be used in everyday productivity software. It’s suitable for a range of roles – from developers and IT professionals to business users – and is a great way to upskill teams using resources provided by a major AI technology provider.
Google Cloud – Introduction to Generative AI – Offered via Google’s Cloud Skills Boost platform, this learning path gives a hands-on introduction to generative AI techniques. It covers the basics of building and using generative models (the kind behind tools like ChatGPT) in an accessible way. For organizations interested in leveraging AI for content creation, coding assistance, or data analysis, Google’s Introduction to Generative AI path can help employees grasp how these models work and how to apply them. It’s an excellent follow-on for teams that have the basics down and want to delve specifically into modern AI advancements like large language models.
LinkedIn Learning – Applying Generative AI in Business – LinkedIn Learning offers a curated learning path for business professionals focused on practical generative AI skills. This program consists of several short courses (totaling around 5–6 hours) that demonstrate how to use AI tools to enhance daily work tasks. Topics include understanding current generative AI tools, using AI to increase personal productivity, basics of prompt engineering (crafting effective queries for AI), and real examples of applying AI in marketing, sales, and other functions. It’s well-suited for teams that want to quickly learn how to incorporate AI assistants into their workflow to save time and improve results. Learners can immediately apply tips like using AI to draft emails, summarize reports, or brainstorm ideas.
Each of these courses addresses AI fluency from a different angle – from high-level overview to hands-on tool use – so you can choose what fits your organization’s needs. Encouraging your employees to take one or more of these courses (and allotting them time to do so) can rapidly raise the overall AI proficiency of your workforce. The goal isn’t to turn everyone into AI engineers, but to ensure they understand AI basics and know how to leverage AI tools relevant to their roles. With a solid foundation from these programs, employees will be more confident and competent in using AI on a day-to-day basis, which is a critical step toward achieving an AI-fluent organization.
Measure AI Fluency with Worklytics
After investing in building AI skills, how do you know if it’s paying off? Measuring the actual uptake and usage of AI tools in your organization is the next crucial step. This is where Worklytics comes in. Worklytics is a people analytics platform designed to help organizations measure how work gets done – including the adoption of AI tools.
In essence, it serves as an AI fluency dashboard for your company, turning abstract goals of AI adoption into concrete data.
Key insights Worklytics provides include:
Adoption Rates and Gaps: See at a glance who is (and isn’t) using AI. You might discover, for instance, that your engineering team has high AI adoption while your sales team lags. Such insights let you target follow-up actions – maybe a refresher workshop for the sales department – to boost overall fluency.
Identification of “Power Users”: Worklytics can identify individuals or teams that are far ahead in using AI (the AI champions in your organization). By spotting these power users, you can learn what they’re doing differently and share those practices company-wide. Recognizing and empowering your AI early adopters helps in creating internal AI evangelists who inspire others.
Usage Trends Over Time: The platform tracks trends in AI usage over weeks and months. Perhaps Marketing’s AI usage surges after they attend a generative AI webinar – you’ll see that in the data. If a certain tool isn’t catching on in one department, that trend will be visible too, prompting a deeper look or a switch in approach. Trend data ensures that AI fluency is not a one-time checkbox, but an ongoing journey you can nurture.
Sample Illustration of Worklytics in Actions taken by agents per week
Impact and Productivity Correlations: Beyond raw usage, Worklytics helps connect AI usage to outcomes. It can correlate metrics like AI tool usage frequency with performance indicators such as project completion time, sales growth, or customer service response rates. This is powerful – it closes the loop by showing whether increased AI fluency is translating into real business results. For instance, you might find that teams who heavily use a coding assistant are releasing features faster, or departments using an AI writing tool have higher client engagement. These insights give executives concrete evidence of AI’s ROI and pinpoint where it’s making a difference.
Sample Illustration of Worklytics in meaningful insights
Benchmarking Against Peers: Worklytics also allows you to benchmark your organization’s AI adoption against industry peers or internal targets. Are you ahead of the curve or playing catch-up? Knowing where you stand competitively can inform your AI strategy. If you’re lagging behind the industry average in, say, percentage of employees using AI weekly, that might spur a company-wide initiative to step up training. Conversely, if you’re leading, you can capitalize on that advantage and set even higher goals.
Sample illustration of Worklytics in Benchmarking AI usage compare to peers
By consolidating these analytics, Worklytics gives you a real-time pulse on your organization’s AI proficiency and usage. It transforms AI fluency from a vague concept into a clear, data-driven discipline. Armed with these insights, you can celebrate what’s working, fix what’s not, and ensure that your investment in AI tools truly translates into improved performance across teams.
