A Global Collaborative Exercise – The Future of AI

Innovation360 Group has been a power user of Artificial Intelligence for a decade or more. We believe this evolving technology will continue to have significant impact on the world of work and that increasingly sophisticated functionality will be a necessary part of the ‘tools of the trade’.

But from time to time, we wonder about how this will take place, in what form and what impact it will have on actual work?

The rush to integrate Gen AI has led many organizations to prioritize short-term efficiency gains over sustainable long-run business outcomes. While AI in general excels at automating processes and analyzing vast amounts of data, and Gen AI is showing promising results in content creation, its widespread adoption carries significant risks – especially in strategic functions like new product development and innovation. Poorly conceived adoption of Gen AI in these areas runs the risk of diluting brand identity, homogenizing ideas, and eroding competitive differentiation.

To answer those questions, and to explore & understand the current value and pitfalls of AI, its changing dynamics, adoption, and impact we hosted a four-week ‘open innovation’ initiative, collaborating with a group of 20+ professionals from our global network, who collectively work across multiple industry sectors in almost as many countries. The authors want to acknowledge their contributions and assistance in completing this paper. The group included Khaldoun Aboul-Saoud, Marwan Ata, Duccio Cosimini, Samar Diab, Peter Dolenc, Isaiah Engelbrecht, Allan Fors, Peter Glasheen, Cher Gulinao, David Hayes, Kasia Hein- Peters, Peter Junermark, Jogeswara Meesala, Omanh Oman, Kelly O’Neill, David Pettersson, Magnus Penker, Nada Rih, Arthur Scholten, Dr. Satnam Singh, Khoh Soo Beng, Jeremy Staples, Tord Thunman and Niklas Tiger.

Using Innovation360’s unique ideation platform, the group identified 165 unique ideas and consultant stories, which fell into ten thematic buckets or ‘clusters’. Building upon these clusters, we refined the key ideas identified and landed on four targeted views of the main challenges emerging from the use of Gen AI.

Challenge #1: Keeping a Unique Brand Identity & Trust

AI-generated content due its inherent nature (biases, data-sets, reasoning…) risks two key outputs:

  • The generation of homogenous solutions, making it difficult for organizations to maintain a unique brand voice both from a communication perspective and from its offerings. Gen AI relies on existing data, which can lead to clinical, uninspired, and non-differentiated Organizations that rely too heavily on AI- generated uninspired content risk producing material that lacks originality, strategic depth, and true market relevance.
  • Gen AI can amplify inaccuracies and biases, and the potential implications for trust in AI-generated outputs. Organizations generate massive amounts of data, but if Gen AI is used without informed human oversight, errors and misinformation can propagate at scale.

Challenge #2: Avoiding Workforce Disengagement

The paradox of automation suggests that while AI can boost short-term efficiency, it may also lead to workforce disengagement over time. By automating too many tasks, particularly those that offer intellectual challenge, employees may feel disconnected from meaningful work, reducing motivation, innovation, and long-term productivity.

Challenge #3: Ensuring Strategic Context

AI’s effectiveness is limited by the data and parameters it operates within. Without proper context, AI- generated outputs may be misaligned with organizational goals, customer needs, or evolving market dynamics. AI must be highly guarded by clear business problems and integrated into structured innovation management processes to ensure that insights are actionable, contextually relevant, and strategically beneficial.

Challenge #4: Building an Innovation Culture & Creating Long-Term Value

AI adoption without an embedded innovation culture leads to short-termism and fragmented implementation. Organizations that fail to cultivate a culture of continuous learning, experimentation, and human-AI collaboration will struggle to maximize AI’s potential.

It was with these challenges as a backdrop that this position paper sprung into life. In the following sections, we have elaborated on our observations in the marketplace, coupled it with real-world experience and outlined a guide for how to tackle each identified challenge.

Each of these is discussed in more detail in our position paper “Using Generative AI for Strategic Innovation”. Find out more here:  LINK