Five Levers to Boost AI Through Collaboration

Artificial Intelligence is key for any organisation seeking to create future economic and societal value – but many AI projects fail. Deep-rooted collaboration can help to propel those that want to use AI to advance society as a whole.

While a few large corporates such as Google and Alibaba are skyrocketing with the help of Artificial Intelligence (AI), for the big majority of organisations around the globe AI is far from a success story. According to Gartner, those who have tried it mostly failed – either because projects were designed too big from the outset, delivered value too late, or didn’t have critical employee involvement. The overwhelming majority of those which didn’t even explore AI commonly think they are not ready for it, as the Austrian chamber of commerce finds. In sum, most organisations – especially in Europe – are falling behind on AI. And there is one underlying cause: a lack of profound, multifaceted and inherently human collaboration.

Not leveraging AI is not an option. It is paramount that value-drive corporates are at the forefront of this technology – to boost innovation, but also to understand and shape a technology that has its risks, too.

So how can we create success stories? Our finding is this: If we truly want to leverage AI to generate sustainable business value, to counter climate change with advanced predictions, to ramp up healthcare through hyper-personalization, and to proactively handle humanitarian crises, we don’t need more technical knowledge, we need to intensify collaboration in radically new ways. Here are five levers that will finally make AI a success story – ranging from your organization to the wider society:

“Fight with your Data Scientist!” Currently, Data Scientists and the rest of the organisation typically ignore each other. They speak different languages and think about challenges differently – making it easy to merely co-exist in this very situation. Yet, to create tangible value with AI, both crews need to be in touch, even if it is through productive conflict. Tension allows us to develop common ground for collaboration. Only then, interdisciplinary teams can shape a joint vision and deliver “wow” business value with AI, as research from the Kellogg School of Management shows.

“Leaders, make AI everyone’s endeavour!” AI needs strong momentum to become a success in spite of organisational inertia. This depends heavily on the use cases selected. In order to identify high impact use cases and to bring them to life, leaders must make AI a collaborative, fast-paced endeavour, bringing the relevant stakeholders and backgrounds together – techy and business-savvy, old and young, coders and designers, even shopfloor workers. AI needs more leadership, not less. I have personally experienced the e-commerce unicorn Berlin Brands Group as a prime example of building an AI Factory along a Community of Practice: From evaluating and productionizing use cases to enhancing AI capabilities across all levels of the company, they are accelerating their growth journey as a collective of AI change agents.

“Come up with radical new partnerships!” Why should an e-commerce unicorn and a mid-sized steel parts manufacturer collaborate around AI? Well, Machine Learning is a method that is not tied to an industry or sector. A Recommender System can take sales to the next level – irrespective of the industry. Similarly, churn prediction can help large international NGOs and telecommunications companies alike. We need more hubs like Germany’s Civic Innovation Platform that not only bring AI companies together but enable unconventional collaborative partnerships for breeding ideas and to learn from each other’s insights.

“Bring data to those who truly create impact!” The public sector, large corporates, health insurers – all of them have big data. Yet those who could innovate with this very data are often nimble AI start-ups that challenge the status quo of how we interact and deliver value. Yet, without data this effort is bound to fail. We need new forms of collaborative data sharing between ML researchers, big incumbents, start-ups, and the public sector – that treat each participant fairly. Kaggle or the European Health Data Space initiative are a solid start.

“Finally, deepen collaboration between AI and humans!” Yes, we must also rethink the way humans and AI interact. Only once we make this a mutually benefitting relationship, AI will become a success story. A recent study from Harvard with more than 1,500 firms finds that real impact is only achieved by combining “the leadership, teamwork, creativity, and social skills of humans, and the speed, scalability, and quantitative capabilities of AI.” Humans and AI need to collaborate as partners.

Deep-rooted collaboration will help us leapfrog the few large corporates and propel those ahead who want to advance society as a whole. Let’s unlock our collaborative capabilities to leverage innovative and responsible AI for the challenges and opportunities of this and coming decades.

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