With AI becoming an increasingly important component of work, many business leaders are grappling with the question of how to implement it, foster its adoption, and understand how to use it to drive meaningful outcomes. In fact, data from Asana’s Work Innovation Lab reveals that nearly half of UK knowledge workers use generative AI on a weekly basis, a significant increase from just 29% nine months earlier. This rapid rise in AI adoption demonstrates how optimistic workers are that AI can help drive efficiency.
But that also means more pressure on leaders to implement AI solutions that help meet business goals, increase revenue and boost productivity – 90% of IT leaders even say investing in AI technology will be critical to meeting future business challenges.
Unlocking the potential of AI is more than a technological challenge. It is a critical strategic priority that companies must meet in order to compete in today’s marketplace. With this in mind, I share my advice as an AI product leader to help executives build a foundation for AI now, guide and inspire teams along the way, and start delivering results for the future.
Product Manager at Asana.
1. Develop AI principles that underpin everything you do
The potential of AI is huge, but organizations without a strategic approach risk producing more content, more tasks, and more work as siloed teams incorporate disparate AI tools. To combat this disconnect, it’s important for leaders to design a strategic approach for the entire organization, outlining how AI can be used, how it should be used, and ensuring teams are informed. When you have a clear set of AI principles, it’s easier to determine how and what to move forward.
There are a few important things to keep in mind when designing AI principles. First, you need to embed people in everything you do—we call this the human-centered approach to AI. AI should enhance people’s natural capabilities and help them achieve their goals, not replace them. When AI automates routine tasks like status updates and research, people are empowered to do more impactful work that drives change. Second, with any AI your organization uses, make sure people are the final decision-makers and that they understand how AI informs recommendations, content, and strategy. Next, prioritize transparency. Whether it’s your teams or your customers, everyone should be able to easily understand how AI is being used in your organization. And finally, take AI safety seriously and make sure you balance the speed of AI deployment with responsible use.
AI has the power to make work better, more enjoyable and more productive, so people can focus on what they do best – creativity, innovation and strategic thinking. Up to two-thirds of workers using AI say they are more productive, demonstrating how much more teams can achieve when AI is deployed effectively.
2. Provide AI training and guidance for teams.
Many knowledge workers feel uncertain and anxious about the role AI will play in the workplace and how it will impact their jobs – one in three employees fears AI will replace human workers. It’s important for leaders to make teams comfortable with using AI so they can focus on high-impact work that drives results, not routine work that can be easily automated and streamlined with AI.
Today, AI training is one of the most important career opportunities leaders can offer their teams, yet fewer than one in five UK employees (17%) say their organisations have provided it. Leaders must work to create a safe environment based on formal training where employees can try and experiment with AI, because that is the best way to learn.
The most important thing employers can do to help their teams learn about AI is to allow them to experiment and experiment. You can’t teach someone the art of what’s possible – they need to have that moment of revelation to fully understand the power of AI, as well as its limitations. This kind of exploration also helps people learn how to give prompts, re-prompt, and repeat them with AI to get the best possible results over time.
3. Prioritize data accuracy and structure
Data will unlock the potential of AI to move work forward, but our research shows that the accuracy of AI outcomes is the biggest concern for knowledge workers, with only 39% of IT leaders expressing a high degree of confidence that their organization’s internal data is AI-ready. Without accurate and reliable data, organizations will be unable to use AI to deliver critical outcomes.
Leaders must prioritize improving data quality so they can test and evaluate how AI can help them achieve better outcomes. That means product leaders, data scientists, and lead architects must work closely together to ensure the data informing the AI platforms they use is structured, reliable, and accurate—not the piles of in-process documents, emails with conflicting updates, and siloed messages in messaging apps that so many teams operate with.
And while data about the work within your organization needs to be accurate, it’s equally important that it is clearly connected to the people doing the work, cross-functional teams, and your organization’s higher-level goals.
Prepare your organization for the future with AI
It’s easy to be intimidated by AI, which is why I always encourage other leaders to get started. It can be as simple as testing new AI platforms in your workflow, while working toward creating clear and transparent AI principles for the entire organization. But the most important thing is to find a way to start now, experiment with new use cases, create champions across the organization, and keep moving forward from there.
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