Insight
How Artificial Intelligence is Reshaping Organizational Collaboration and Culture in Innovation
October 30, 2024
Tina Asmuth Chatalas
This article is the second in a two-part series from an interview conducted by NextAccess Senior Partner Tina Asmuth Chatalas with Dr. Ted Ladd on how generative AI (gen AI) is changing innovation. Gen AI is not only accelerating innovation and speed to market, as we discussed in our last article, but it is also reshaping organizational collaboration and innovation culture. The future of innovation isn’t just about smarter machines - it’s about smarter, more connected, more empowered people.
Ladd is a professor of Entrepreneurship and Innovation at Hult International Business School, an instructor of Platform Entrepreneurship at Harvard University, and a veteran of seven Silicon Valley start-ups.
For years, corporate America has grappled with the challenge of “silos” - those invisible but formidable barriers that keep departments isolated, information trapped, and innovation stifled. Departments like marketing, finance, R&D, and operations often worked with limited collaboration. Even when they did come together for innovation co-creation sessions, it was often a one-off and hard to keep the momentum consistent.
Generative AI (gen AI) has the potential to accelerate innovation, as we discussed in our last article (Part I: The Role of Artificial Intelligence in Accelerating Innovation), and also reshape an organization’s culture of collaboration. According to Dr. Ted Ladd, professor of entrepreneurship and innovation at Harvard and Hult, “Gen AI is not just a technical tool—it’s a cultural change agent with the potential to redefine how businesses operate.”
““Gen AI is not just a technical tool—it’s a cultural change agent with the potential to redefine how businesses operate.””
Holistic Idea Generation: Breaking down Silos to uncover innovation opportunities
At the heart of this cultural transformation lies the dismantling of traditional data silos. In many organizations, departments operate separately with their own objectives, methodologies, and data sets. This fragmentation slows the free flow of information and ideas. The result? Missed innovation opportunities. However, gen AI can change this dynamic. By pulling from multiple data sources across departments, gen AI consolidates insights and offers a holistic view of the organization, enabling new ideas to come forward as well as more cohesive decision-making.
To maximize the impact, companies need to move to data pools. Ladd says, “We need to move from data silos, not just to a data reservoir, but to a data pool where everything is coded in a way that gen AI can look at all of this at the same time. Finance and marketing typically don’t have the same data. These datasets are rarely formatted the same way. The datasets in these systems can’t talk to each other because they never needed to before AI.”
Small Language Models (SLMs): A New Way to Leverage Inter-Departmental Insights
Progressive organizations are moving towards these integrated data ecosystems, where information flows more freely across departments. This interconnectedness enhances the capabilities of gen AI systems and also enables new levels of interdepartmental collaboration. Small language models (SLMs) can be customized for company-specific needs, allowing teams to work with relevant data that would have previously been siloed or overlooked.
As Ladd explains, “This data can all go into a ‘small’ language model (SLM). However, with increasingly powerful AI engines, these models are not that small anymore. They can now include everything the company does. AI using these models can uncover innovations that are feasible for the company to build and that have measurable financial impact.”
Gen AI also brings departments into the innovation process that have not been systematically included previously, such as customer service representatives, field technicians, and sales personnel. With gen AI, these employees can contribute solutions based on their direct interaction with customers that are efficiently integrated into the data sets and that may have been previously overlooked.
Ladd says, “Frontline salespeople have unbelievable insights about what customers want, but typically nobody asks them. However, if we could pick their brains and put their observations into a database, making them feel valued as a source of insight for innovation, we will have changed the culture of the company.”
SLM Definition:
Gen AI models that are tailored on specific domain knowledge, organizational contexts, information and customer segments with cross-departmental data.
AI as a Cultural Change Agent - The Permissionless Corporation - Management as Coaches
This democratization of innovation is at the heart of what management theorist Rita McGrath, based at Columbia University, calls the “Permissionless Corporation.” This approach advocates for a flattening of traditional innovation hierarchies in favor of a more fluid, collaborative approach to problem-solving. “What she is saying,” says Ladd, “is innovation can come from anywhere. Indeed, innovation must come from everywhere for a company to stay competitive.”
This cultural shift also changes the role of leadership. In this new landscape, leaders need to evolve from gatekeepers to coaches, fostering environments where experimentation and iteration are the norm. However, leadership can't stand on the sidelines when it comes to understanding gen AI. In order to effectively coach their teams, they have to be gen AI practitioners, familiar with it’s strengths and limitations. Ladd explains, “If you are an executive in a company trying to figure out how to take a product to market, you soon realize that you plus gen AI is better than gen AI alone and is better than you without gen AI.”
Of course, change of this magnitude doesn’t come without some resistance. Concerns about job displacement loom large in many minds. But Ladd is optimistic, drawing a parallel to another transformative technology. “I don't think AI is a job killer in the same way that the arrival of the automobile wasn't a job killer,” he argues. “ Yes, all of a sudden, people making buggy whips were out of work, but with the arrival of the car we had car manufacturing, the oil and gas industry, and then we had a highway industry. I believe gen AI is going to have the same impact. We're going to have an enormous number of new jobs.”
““What she is saying is innovation can come from anywhere. Indeed, innovation must come from everywhere for a company to stay competitive.” ”
““If you are an executive in a company trying to figure out how to take a product to market, you soon realize that you plus gen AI is better than gen AI alone and is better than you without gen AI.””
Recalibrate Success Metrics
As organizations embrace this new culture, they’re also grappling with how to measure success. Traditional key performance indicators may feel inadequate in the face of gen AI’s far-reaching impact. Forward-thinking organizations are exploring more holistic measures, ones that consider not just financial outcomes but also broader societal impacts as well. This expanded view of success often aligns more closely with employee values, potentially driving increased engagement and retention.
Creating Dynamic Innovation Environments
Companies that successfully navigate this transformation stand to create more dynamic, inclusive, and ultimately more innovative environments. However, the road ahead is not without challenges. As detailed in a recent article by NextAccess Senior Partner Marcy Schwab, “Change Management has Changed Forever,” this kind of transformation requires “an intentional strategic shift” and a reimagining of change management itself.
The potential rewards of doing so are substantial. In an era where innovation is often the key differentiator between market leaders and followers, the ability to harness gen AI effectively within a company’s culture may well become the defining characteristic of successful enterprises. As Ethan Mollick, Co-Director of the Generative AI Labs at Wharton, notes, “If you are waiting for use cases to be given to you, you are going to wait for all of your competitors to squeeze value out of current AI systems - and to be better positioned for the next generation. AI is not being built for your use case. It is a general technology to adapt.” The future of innovation isn’t just about smarter machines - it’s about smarter, more connected, more empowered people.
Want to explore ways to foster more innovation at your company? Please reach out to Tina at tina.chatalas@nextaccess.com
Tina Asmuth Chatalas is a Senior Partner at NextAccess, a boutique strategy consulting firm that delivers advanced go-to-market solutions for executive leaders. Our team of experienced operators has a track record of leading successful sales, marketing and innovation transformations at global companies across industries. At NextAccess, we bring a unique mix of strategic insight, operating experience, analytical rigor, and sophisticated AI capabilities to drive tangible results for our clients. We cut through the noise to grow revenue and margin by harnessing the best in artificial – and human – intelligence.
Tina has led growth strategy and innovation projects for Fortune 500, middle market companies and start-ups in the US, Europe and Asia. Her passion is finding untapped opportunity at the intersection of consumer insights, market trends and corporate strategy.
Dr. Ted Ladd is a professor of Entrepreneurship and Innovation at Hult International Business School, an instructor of Platform Entrepreneurship at Harvard University, and a veteran of seven Silicon Valley start-ups, including the IPO of Palm Inc, where he did the first acquisition of an App Store and an ebook reader. Ted also worked on smartwatch software that was acquired by Google, rebranded WearOS, and currently powers watches from over 40 brands. He is a board member of an electric utility, a venture studio, an economic development agency, and an environmental non-profit.
Ted’s research, detailed at ORCID, Google Scholar, and his Forbes column, focuses on how AI impacts the strategy of multi-sided platforms. His most recent book, Innovating With Impact, was published by the Economist.
