By Rebecca Hinds, Head of Asana’s Work Innovation Lab
The adoption of artificial intelligence (AI) is accelerating at a remarkable pace. According to Asana’s Work Innovation Lab, almost half (48%) of UK workers now use generative AI tools on at least a weekly basis. Moreover, the benefits seem to multiply with more frequent use. Daily AI users report the biggest gains, with 88% experiencing a productivity boost.
But adopting AI isn’t a one-time task. It requires a shift in culture and management that extends far beyond technology adoption. And since no two businesses are the same, the challenge lies in figuring out the right moves for your business.
My team at The Work Innovation Lab has broken down the journey of AI adoption into five stages, ranging from early-stage scepticism to fully-fledged maturity. Progressing through these stages involves investing in resources, training, and robust policies, all while prioritising safety, reliability, and a human-centric approach. Do these actions well, and your organisation can unlock significant productivity gains, deploying AI more broadly and with greater impact across your organisation.
Where are you now?
If you’ve only just started to think about AI’s potential and are toying with the idea of running a few pilots, you’re at the first stage of AI maturity, Stage 1: Scepticism. This initial period is about exploring the possibilities AI can offer. Each subsequent stage—Activation, Experimentation, Scaling, and ultimately, Maturity marks a step forward in aligning AI’s capabilities with your organisation’s strategic goals.
No matter where you fall on this AI maturity scale, you’re likely butting up against a few roadblocks. These obstacles tend to fall into what we call “the five C’s”:
- Comprehension: How well your employees understand and use AI.
- Concerns: The level of apprehension or resistance they have toward AI.
- Collaboration: How effectively employees interact and collaborate with AI.
- Context: The policies, principles, and organisational frameworks that shape AI’s role at work.
- Calibration: The methods used to measure AI’s impact and effectiveness.
Once you have this framework in place, you’ll find it much easier to take meaningful, targeted steps to advance your AI journey.
Taking steps
Now that you know where you stand on the AI maturity scale, it’s time to chart your next steps for thoughtful adoption. When it comes to comprehension, the goal is to improve AI knowledge and skills. Half of UK workers (50%) are already proactively learning about generative AI through personal experimentation, often without formal training. While it’s crucial to empower and support these self-motivated individuals, the responsibility of upskilling shouldn’t rest solely on employees’ shoulders.
Prioritising AI literacy, training, and development requires a collaborative effort between employees and companies to equip teams with the tools and knowledge they need to use AI effectively. This could involve AI literacy programs and education initiatives that establish a solid foundation of understanding around AI and its applications. With a more knowledgeable workforce in place, mentoring can help cultivate a culture of continuous learning. You should also encourage hands-on learning by creating “safe zones” where experimentation is welcomed, and mistakes are seen as part of the learning process—this builds both confidence and proficiency.
Improving comprehension directly helps in addressing concerns, that second “C.” As comprehension around AI increases, myths and preconceived biases often fade. However, concerns about unreliable AI can only be effectively addressed by choosing tools from trusted vendors and investing in high-quality data pipelines and robust governance practices. Similarly, ensuring that AI technologies are accessible and easy to steer is essential to alleviate any concerns about their interpretability and usability.
More than a machine
As businesses progress in their AI journey, their perception of AI’s role within the team evolves. In our research, we’ve found that while people start by seeing AI merely as a tool, they gradually shift to viewing it as a collaborator—a teammate. This mindset shift isn’t just philosophical; it’s practical. Workers who see AI as an integrated teammate, rather than just another tool, are 33% more likely to report productivity gains from using AI at work.
Encouraging this more integrated mindset leads to broader and more creative applications of AI. Instead of being relegated to menial tasks like notetaking and summarising, AI begins to contribute to brainstorming sessions, problem-solving, and offering decision-making suggestions.
To foster this kind of culture, it’s crucial to establish the right organisational context—that fourth “C”—which involves comprehensive AI policies, principles, and guidelines. These provide the framework for your company’s long-term AI ambitions and ensure that resources are committed to its adoption and continuous use. Equally important is setting clear metrics that align with business objectives, allowing you to track and calibrate AI’s performance—the fifth “C.” These metrics don’t just help demonstrate ROI—they also pinpoint underperformance and highlight areas that need refinement. For example, if customer service representatives find that an AI chatbot is consistently misunderstanding certain queries, this feedback can be used to retrain and improve the AI model.
A framework for successful AI adoption
Adopting AI isn’t just about rolling out new tools and crossing your fingers for a productivity boost. It takes a mindset of continuous learning and relentless improvement. Using the five “C” framework and with solid backing from leadership, businesses of any size can not only adapt but excel as they integrate AI into their operations. Those who double down on investing in their people, fine-tuning their processes, and choosing the right AI tools will be the ones to reap the real rewards of a more efficient and innovative business.
