Mainstream AI has arrived, and with it all the questions about what this means for our jobs and our businesses.
Which tasks are best handled by humans, which do we want to hand over to AI, and which are most effective through some kind of human-AI collaboration? Will leaders need to up-skill entire workforces? And will all this make work better?
It’s easy to feel overwhelmed by the pace of change. But, equally, now is not the time to take a back seat to wait and see what happens.
The reality is that we’re living in the early days of the autonomous age, and we need to make some key decisions now in order to thrive later. First, businesses need to embrace the uncertainty by experimenting with how AI can be a trusted sidekick in the workforce — improving not just our productivity, but the work itself. Then, they need to reward transparency and insight-sharing to ensure that all teams within the organization can benefit from this new technology.
Why it’s important to experiment with AI
Author and Wharton Business School professor Ethan Mollick said, “As artificial intelligence proliferates, users who intimately understand the nuances, limitations, and abilities of AI tools are uniquely positioned to unlock AI’s full potential.”
Mollick encourages his readers to always invite AI to the table as a collaborator. Now is your window of opportunity to explore its potential. AI is good at brainstorming, never running out of ideas. It can also help people break out of a creative block, alleviating the blank canvas problem by giving your team a starting point to edit or react to.
We’re also discovering how AI has the power to speed up and improve the quality of work. In one study, Microsoft found that the AI tool GitHub Copilot helped programmers complete tasks 55.8% faster.
As a research collaborator or personal assistant, AI can build off the work you’ve already done to synthesize research, summarize a meeting, give feedback on a presentation, or generate more ideas.
For instance, Miro’s AI Sidekick tool can take user stories on your board, synthesize insights, and create acceptance criteria for them. When you hit a wall, AI can be there as a collaborator to bounce ideas off. Not every idea it generates will be a winner, but a surge of ideas can help the creativity flow. But first, we have to learn how to integrate it.
I believe that the best approach right now is for each of us to experiment with AI to find the best value for ourselves, our jobs, and our businesses. AI is better than humans at some things, like analyzing large data sets or text, but limited at others, like critical thinking and judgment. By experimenting, we can learn where the technology adds value and where it falls short.
It’s not about having all the answers right away; it’s about being prepared to ask the right questions, pay attention, and adapt quickly.
How to build a culture of AI experimentation at your company
Building a culture of experimentation takes creativity and trial and error. Generative AI isn’t like typical software, programmed to do simple and predictable tasks. It’s more unpredictable and infinitely more capable, so its complexity requires nuanced thinking and analysis.
We must encourage a culture of experimentation and testing amongst employees, but balance it with time for assessment and reflection.
Here are some ways to promote thoughtful experimentation:
- Have discussions about AI’s role within your organization and be transparent about what AI means for your business.
- Build in retrospectives and set frameworks for assessing the outcomes of AI experimentation.
- Set up internal committees to create an AI infrastructure, monitor regulatory changes, and adapt your culture.
As you experiment, keep in mind that AI will only improve, so think more about the potential than the limitations of the current models.
Create incentivization models for insight-sharing
One important way that we can promote innovative AI adoption is to create a culture of transparency and incentivize employees to share their insights.
Right now, if someone on your team discovers an AI hack that saves them two hours of work a day, what incentive do they have to share it broadly? If you don’t currently have any, set up reward structures, speaking opportunities, or AI hackathons to encourage data-sharing and collaboration.
Here are a few things we do at Miro to incentivize insight-sharing:
- We send out a regular newsletter about how employees across teams are experimenting with AI
- We share prompts and video explainers with both good and bad examples of experimentation to contribute to our collective learning
- We’ve also appointed our Director of Business Transformation, Tomás Dostal-Freire, to spearhead and champion AI transformation at Miro
Construct frameworks for stakeholder transparency, ethics, and regulation
As you press into AI adoption and experimentation, build frameworks to lead your company into the autonomous age with leadership and intention.
1. Transparency
Transparency is key for internal alignment and growth, but it’s also important for external stakeholders. As you deepen your AI maturity, consider if and how you will disclose AI use to customers, shareholders, or community partners.
2. Ethics
Questions about creative ownership, privacy, cybersecurity, and risk require serious consideration from every company adopting AI. Just half of companies have AI guardrails in place, opening the doors to individual employee interpretations of fair use.
Many global leaders are developing responsible AI (RAI) principles to plan for ethical questions and emerging policies and regulations. When CEOs participate in RAI planning, businesses realize 58% more business benefits.
3. Regulation
Even fewer companies (38%) are planning ahead for AI regulation. The EU AI Act took effect on August 1, 2024, marking the first big legislation governing AI use — and certainly not the last.
Taking a wait-and-see approach isn’t an option for a competitive business. Instead, consider setting up a steering group to monitor regulation, anticipate challenges, and share guidelines within the organization.
How to achieve better work (and happier teams) with AI
It’s clear that AI can help us work faster. Azeem Azhar calls this the “cognitive productivity pill.” However, if you think the end goal of AI is to cut time or costs by 15%, you’ve missed the point. Don’t make the mistake of filling freed-up time with more of the same work.
Instead, think about how you can reinvent work at its core and make it more meaningful. Most professionals using AI say it lets them spend more time on the creative aspects of their job (83%), and on the parts of their job they enjoy the most (83%). AI’s full potential means empowering humans to improve our work quality, make better decisions, and be more creative.
This shift has the potential to solve a big problem in workforces today: employee disengagement. A survey by Chief Executive found that employee retention and engagement is the top issue worrying CEOs in 2024. When people are bored or don’t like their work, they may quit.
AI can be a tool to improve attrition, not reduce headcount. Eighty-two percent of executives surveyed by Deloitte expect AI to increase employee engagement. Another 68% are retraining and upskilling employees to take on AI roles. With AI, we can find ways to reduce repetitive tasks and help employees engage in more meaningful, collaborative, and creative work.
How a thoughtful AI strategy can transform work
Paraphrasing researcher Roy Amara, we tend to overestimate the effect of a technology in the short term but underestimate it in the long term. As we stand at the precipice of enormous change, it’s clear that AI’s promise extends far beyond efficiency gains. While we don’t know what the autonomous future will look like, we know it will be exciting and new. So, let’s take the opportunity to lean into it, experiment with new ideas, and unlock opportunities for creativity and better work.
