I take my seat and see the artefacts placed throughout the room. They give me some clues of what is about to happen. There is a big screen with a presentation slide welcoming us, the facilitators are at the front ready to guide us. In piles around the room are colourful post-its and thick felt pens. Rolls of tape and sticky tack gives a hint that probably more papers will join the ones already on the walls. All the ingredients are there for a traditional creative human-to-human collaboration workshop. I sit down next to a friendly looking guy, with a post-it pad in his hand. Pointing to the post-its with his marker he says: “Now we are all set to be creative” and laughs.
In the first workshop I spent most of my energy trying to understand who the others in the room were and what they believed in. This is probably quite a common focus in a human-to-human workshop, where we as humans try to figure out the social context we are in. We learned about each other by sharing expectations, reflecting on the individual pre-work we had submitted, and were introduced to the process we were to use by moving along the walls from activity to activity, co-creating and making sense together. Slowly we got to know each other better, finding common interests and challenges resulting in interesting discussions and new connections.
On my way home from the first workshop I felt inspired and full of curiosity about the questions my fellow core contributors and I are considering about AI-infused platforms and work in the future. By the time I leave the workshops three months later, I’ve begun thinking about a meta-question about work and AI: where were the AI collaborators in our creative Collaborative Foresight cycle, and what would this creative, collaborative work have looked like if AI had been one of our core contributors?
AI and group collaboration today
Throughout the workshops, we scanned for signals to give us insights into the futures of work. Amongst the signals the group shared were AI as romantic partners, digital work assistants, digital twins and coaches. Many of the signals reflected different humanisations of AI—giving the AI a custom look and feel, designing it to be just perfect for one’s own needs. Making the interfaces more human, might be a way to help us make sense of the technology to better understand and find ways to collaborate with it.
In the foresight work we shared how we collaborate with AI-infused platforms in our daily work, how and when we use them. The personal drive for many to use AI were curiosity, the playfulness of the interactions and a wish to learn new things. Many used it in their free time and some used it at work.
One thing that the core contributors of the group agreed on, across industries and sectors: using AI was about saving time. Individual productivity gains were the red thread. Most signals and references referred to the AI as an assistive agent—some as an intern or an executive assistant, some as a team member. There were a few mentions using AI for idea generation, supporting in creating workflows, concept development and analysis work. What stood out the most to me was that a majority of people worked with AI individually, and primarily in the afternoons or the evenings. It seemed that AI was rarely involved in group collaborations, and there were very few examples of AI as a collaborative partner or agent for change in our respective collaboration processes, empowering human collaboration.
I believe that the key to inclusive AI platforms is people. Imagine the opportunities developing AI-infused platforms for work that build on the personal drive, curiosity, the playfulness of human interactions, the wish to learn new things, and combining it with co-creation in teams. Coming together with your colleagues to shape new ways of working together with AI could speed up the design and successful implementation and adoption of collaborative AI platforms at work.
Changing how we change
Harvard professor Karim Lakhani, who specialises in workplace technology and particularly AI, says that the challenges companies are facing are 30% about technology, but that the real challenge is 70% which is an organisational challenge. In a talk with the Harvard Business Review from 20231, he describes how “every executive, every worker needs to have a digital mindset, which means understanding how these technologies work, but also understanding the deployment of them and then the change processes you need to do in terms of your organisation to make use of them.”
AI is changing the tasks we do, and how we do them. A prerequisite for the success of “making use of” AI as a collaborative workplace technology is to invite people to learn and to contribute to the shape and use cases of AI, from an organisational perspective. My experience as a change manager is that a successful implementation of new workplace processes —especially those that rely on new technologies— is always to start with the heart. I call it “heartskilling,” a more human-centred counterpart to upskilling (which makes me think of simply upgrading a robot). By involving and inviting people to collaborate to the change process early through playful testing and creative learning with new work tools like AI, organisations lay the best foundation for both successful deployments of and successful investments in new workplace technology.
I learned about the importance of heartskilling from a senior colleague, who told a story about a cake mix manufacturer who released a new type of cake mix that didn’t need eggs. When the mix launched, the sales dropped dramatically. The company tried to figure out what was wrong. Was it the new recipe, or maybe the communication around it? After some investigative consumer research, it turned out that customers didn’t feel like they were baking if they didn’t get to crack an egg into the mix.
When implementing new tools and ways of working, I try to always leave some space and encourage leaders and co-workers to fill that space in a way that makes sense for them. This makes sure that they are part of baking the cake together, making improvements to the tools and processes. It’s important to not just implement ready solutions, so teams can tweak the tool or find aspects of the process that a central development team never would have thought of.
I have worked with all steps of business development from explorative innovation research, iterative prototyping to development and implementation. For me the red thread is always people. Involving people from the beginning and throughout the whole process ensures not only a relevant and efficient product, it also builds a foundation for successful implementation and change management.
Looking at the opportunities connected to AI-infused platforms for work I see an immense opportunity to co-create the tools and how a team will relate and collaborate with it. The integration of AI-infused platforms, many connected to easy to use generative AI interfaces, can be adjusted by people using them making playful, inclusive implementation of collaborative work tech a great change management opportunity that can be inclusive and inviting to all types of users.
The barriers to introducing new workplace technologies are lower than ever when workers do not need tons of training or a team of tech support or developers to adjust new digital tools into their workflows, or to design the kind of interactions they want to have with them. As AI tools adapt to and learn from humans, the training and design becomes part of the change management process already from the begnning. Inviting teams to collaboratively build their new workplace tools also shapes how they would like to relate to them— individually and as a team.
If AI was a collaborator in Collaborative Foresight
Back at Media Evolution, we are gathered again in a big room, chairs in a half circle, papers on the wall, colourful post-its and felt markers surrounding us. The facilitators are standing in the front and we all reflect on the experience of the Collaborative Foresight process. I keep coming back to my thoughts about the collaborative, creative AI agent.
The Collaborative Foresight facilitators have used AI tools through the process to support more clerical work: summarising the group’s thoughts, and turning our group reflections and voiced messages into text. But at one point, the draft text of our collaboratively-described futures are used to generate images. One image of “digital hippies” made everyone laugh, and that image and the response it provoked really stuck with me after the workshops. That AI-generated picture didn’t just summarise what we had written—it added something to it. The picture prompted our group to take our foresight work to the next level. It made me think about what using a collaborative AI agent in this creative foresight work could have been.
If AI was a core contributor in Collaborative Foresight
The work through AI had already begun before we core contributors stepped into the room that October morning. As part of the workshop pre-work, our ‘digital twins' had emailed signals to the facilitators, and had accessed ongoing global discussions happening around those signals, before we met. When twenty core contributors walked into the room, we started with something more than the sum of all individuals’ contribution: printed papers on the wall shared our collective knowledge as a starting point, where our facilitators curated everyone’s contribution and opinions to help us find a couple of different viewpoints to challenge us or to build on.
Both in big group settings and small group work, we relied on voice assistants and devices to search for, confirm, inform, and guide us with foresight tools, methods and general info on using them. And our facilitators’ roles changed: moving from leading and introducing exercises to facilitating human-to-human-through-AI dialogues, iterating on our work with AI tools, and building AI agents into what we needed, as individuals and as teams.
The colourful artefacts of post-its and markers played an important role in the collaborative work, anchoring the digital work into the analogue place we were in. Meeting in a physical space emphasised the human-to-human connection and the physical aspects of collaborating, using our body language to be inclusive and to focus on listening to each other.
In Closing
Going into the Collaborative Foresight process about digital work and AI-infused platforms I knew that we were standing in front of a great shift in work. I had some thoughts about the topic but struggled with understanding how it could go from discussions and thoughts into implemented solutions in daily work. Through discussing and playing with our scenarios, I found the link that was missing for me—the human touch. Many discussions around the futures of work and AI are about technology alone, and how it might replace human labour. Very few are about how we practically will make that transition in organisations in an inclusive, humane way. We need to learn by doing to figure out how we can make AI a collaborative partner—a meaningful core contributor to our work—not just an individual productivity enhancer.
As a change manager I’m excited about the opportunity to turn curiosity and playfulness into key ingredients in an inclusive collaborative change process, where we as co-workers are part of designing and adjusting our AI partners to add value in daily life. Going into the futures of work, I believe that the challenge ahead is much more about heartskilling—inviting and involving users rather than simply technical, impersonal upskilling. My experience participating in the Collaborative Foresight work has solidified my belief that to help us to learn how to “make use of” AI, will require playful creative collaboration to succeed.
