Experiment, Upskill, and Collaborate: Three Data-Driven Innovation Strategies for Effective AI Integration 

By Frank Henningsen, HYPE Innovation |  June 24, 2024

AI is at the forefront of every corporate conversation, yet leveraging it within organizations remains a mystery in many business areas, including innovation management. As it evolves at hyper speed, the race to innovate and outpace competitors has never been more intense. How can companies turn these obstacles into opportunities? By embracing a bold approach that combines experimentation, skill development, and strategic collaboration. 

Foster a Culture of Experimentation 

Consider this: fail fast and learn even faster. Our latest report with InnoLead, “How AI is Influencing Corporate Innovation Priorities in 2024,” reveals that over 60 percent of companies are increasing their AI budgets and headcounts, underscoring the urgency of this moment. In a world of fast followers and first movers, failing fast is the sweet spot in between. Innovation is about experimentation after all, and if there ever was a time to experiment and fail with AI, it’s now. 

Frank Henningsen, CEO of HYPE Innovation

A culture that embraces experimentation and views failure as a learning opportunity is essential. The report shows that 70 percent of leaders see failures as a normal part of the innovation process or approach them with a willingness to move forward. Encouraging a test-and-learn approach is crucial for effectively integrating AI into business operations. 

By balancing speed with strategic insights, companies can innovate effectively without overcommitting to unproven technologies.

The report notes that many organizations are still figuring out the best ways to leverage AI, with some creating cross-functional communities of practice for generative AI. This approach facilitates experimentation across the organization, allowing teams to explore AI’s potential in various contexts, with a hyper focus on solving specific problems, and learn from the outcomes. 

How do leaders in your organization perceive failures within the innovation program?

At 70 percent of companies, leaders see failures as either a normal part of experimentation, or “with some concern, but willing to move forward.” Source: “How AI is Influencing Corporate Innovation Priorities in 2024.

Being a first mover can offer competitive advantages, but it’s equally important to be a smart mover. The report reveals that nearly one-third of organizations don’t believe they are moving quickly enough with generative AI, indicating the need for a more agile and experimental approach. By balancing speed with strategic insights, companies can innovate effectively without overcommitting to unproven technologies. It’s important to note though, as one respondent put it, “creating a shared understanding that failure as part of innovation is acceptable, but failure cannot stall innovation.” 

Empower People with Essential Skills 

AI’s true potential lies in augmenting human capabilities rather than replacing them. Paul Puopolo, EVP of Innovation at Dallas Fort Worth International Airport, emphasizes that AI must be economical and feasible to be valuable, according to the report. By enhancing human tasks, AI drives efficiency and innovation across various functions. 

As previously highlighted, the report indicates a significant increase in AI-related budgets and headcounts. This suggests that organizations recognize the need to invest wisely in AI capabilities, including in the people who will work alongside these technologies. Despite advancements in AI, the human element remains indispensable. As one respondent explained: “Gen AI will not replace people. Rather, people who know how to use Gen AI will replace those who don’t.” This underscores the importance of human oversight and the necessity for individuals to adapt and learn new skills to work effectively alongside AI. 

Soft skills like collaboration, communication, and adaptability are critical in the AI-driven landscape.

As AI gradually integrates into more and more business operations, both leaders and teams need to develop new skills. Technical skills, such as AI literacy and data analysis, are fundamental. However, soft skills like collaboration, communication, and adaptability (especially when experimenting!) are equally critical in the AI-driven landscape. The report indicates that building strong personal relationships and trust within and between business units is vital for successful innovation, with more than 75 percent of respondents emphasizing the importance of building strong personal relationships and trust for cross-functional collaboration. By fostering these relationships, organizations can ensure that AI initiatives are well-supported and effectively implemented, which leads me to my next point… 

Source: “How AI is Influencing Corporate Innovation Priorities in 2024.”

Facilitate Cross-Departmental Collaboration 

Developing a robust AI strategy isn’t just about adopting the latest technology. It requires careful alignment with the organization’s broader business priorities. Implementing AI comes with significant challenges, including legal concerns, data security, and a comprehensive understanding of AI’s extensive implications. This underscores the need for a future-fit AI architecture — a comprehensive framework that includes the necessary technical infrastructure, policies, and processes to support AI deployment — that is not only technically robust but also flexible, trustworthy, and compliant. 

Developing a robust AI strategy isn’t just about adopting the latest technology. It requires careful alignment with the organization’s broader business priorities. 

Jim Suchara, Senior Vice President at The Doctors Company, advises aligning innovation efforts with the company’s business strategy. He states, “We’re plugged into AI in a lot of different ways. One example is our involvement in overall corporate AI governance. We work a lot with other departments like IT, legal, data governance, and enterprise risk management to develop acceptable use policies, and we help the team identify new AI use cases so they can study them and look at value versus potential risk.” This approach ensures AI initiatives are strategically relevant and mutually beneficial for all business units involved.

According to the report, 53 percent of respondents indicate that the innovation department has significant responsibility for exploring AI use cases, second only to IT, and far more than R&D — highlighting the need for more than just technical capabilities. If Jim Suchara’s approach is any indication, building a future-fit AI architecture necessitates strong relationships between business units. And who better than the innovation team to break down silos and facilitate collaboration between departments? (This is where soft skills really come in handy.) By working together, every business area can effectively overcome barriers and address the pressing demands of AI integration in corporate innovation. 

With regard to AI (artificial intelligence), who has significant responsibility for exploring potential use cases in your organization?

IT is in the pole position when it comes to exploring AI use cases, but the innovation department is not far behind. Research and development holds significant responsibility in one quarter of the organizations in our sample. Source: “How AI is Influencing Corporate Innovation Priorities in 2024.

Navigating the New Face of Corporate Innovation 

As AI continues to redefine corporate innovation, the future belongs to organizations that not only integrate advanced technologies but also cultivate the human touch. It’s not just about adopting AI but about weaving it into the fabric of the organization in a way that enhances creativity in both human-to-human and human-to-machine interactions, decision-making, and operational efficiency. 

Ultimately, the principles of innovation remain constant, but the tools and strategies must evolve. Embrace failure as a learning opportunity, continuously develop new skills, and encourage cross-departmental collaboration. By doing so, organizations can harness the full potential of AI, driving forward into a future where AI and human ingenuity work hand in hand to create lasting value. 

Frank Henningsen is CEO and co-founder of HYPE Innovation.