Strategies for Competitive Edge and Business Growth: Peter Cohan on Unlocking AI’s Potential
# revenue
# Digital Strategy
# Artificial Intelligence
# B2B
Strategic insights from Peter Cohan on using AI to drive innovation, create competitive advantages, and build sustainable revenue growth.
Heather Holst-Knudsen
"AI's real value lies in its ability to drive new growth curves and transform customer experiences, but success requires strategic vision and cross-functional collaboration."
The Revenue Room™ podcast recently featured Peter Cohan, an associate professor at Babson College and a strategic consultant. This engaging discussion explored the transformative impact of artificial intelligence (AI) on business strategies, particularly in driving revenue growth and creating competitive advantages.
Cohan's insights are particularly relevant as we navigate the current AI revolution, which is reminiscent of the early 2000s internet boom but with potentially more far-reaching consequences. While the internet primarily disrupted information flow and marketing, AI is transforming multiple facets of business operations, including work processes, product development, operational efficiencies, marketing, customer engagement, and decision-making.
Understanding the AI Value Pyramid: From Productivity to Innovation
One of the key concepts introduced by Cohan is the "value pyramid," which categorizes AI applications into three distinct levels. At the base level, many companies are using AI to overcome creator's block—essentially aiding productivity but not providing a competitive edge since this application is widely accessible. The middle level focuses on enhancing functional productivity; for example, AI can improve efficiency in coding and customer service by training systems to replicate the best practices of high-performing employees. The top level of the pyramid, which is the rarest and most impactful, involves using AI to create new growth curves that drive significant business transformation and innovation.
Despite its potential, businesses face significant hurdles in implementing generative AI. Cohan highlights several challenges:
• Fear of Reputational Damage: Companies worry about public relations issues stemming from AI errors or hallucinations.
• Balancing Innovation with Risk: CEOs fear being left behind in the AI race while boards are cautious about potential negative consequences.
• Implementation Hurdles: Of the 200-300 AI applications typically developed by large companies, only a handful are released internally or tested externally due to these concerns.
These challenges underscore a critical point: while many organizations are exploring AI applications, few are successfully leveraging this technology to create new growth opportunities.
Real-World Success Stories: ServiceNow and Salesforce
Cohan provides examples of companies that have successfully implemented AI in innovative ways. ServiceNow has rolled out generative AI agents for process automation across various functions. Initially focused on customer service ticket resolution, they have expanded their use of AI to streamline onboarding processes and other cross-functional tasks. This approach not only improves efficiency but also allows employees to focus on higher-value activities.
Salesforce is another company making strides with its Agent Force technology. By employing an agentic approach that enables AI to solve entire problems autonomously—from marketing campaigns to customer service—Salesforce is positioning itself for rapid growth. Early adopters of this technology have reported significant improvements in operational efficiency and customer satisfaction.
The landscape of the AI industry today is markedly different from that of the dot-com era. During the dot-com boom from 1996 to 2001, there were 2,888 IPOs of internet companies; however, there have been no IPOs for generative AI companies thus far. This shift indicates that while startups drove innovation during the dot-com boom, the current wave of AI advancements is largely being propelled by established tech giants operating cloud services platforms.
Leveraging Proprietary Data for Competitive Advantage
Cohan emphasizes that businesses should focus on leveraging proprietary data when developing their AI solutions. This strategy can provide a competitive advantage through unique value propositions that are difficult for competitors to replicate. Additionally, he advocates for cross-functional integration within organizations to break down silos and fully leverage AI's capabilities.
As industries continue to evolve under the influence of AI, several sectors stand out as particularly poised for growth opportunities. The media industry, for instance, possesses rich data environments that can be harnessed effectively with AI technologies. Companies in this space can leverage audience data—from engagement metrics to purchasing behaviors—to create personalized experiences and enhance content delivery.
The insights shared by Cohan during this episode of The Revenue Room™ podcast highlight the critical role of AI in reshaping business strategies and driving growth. By focusing on customer-centric applications, leveraging proprietary data effectively, and fostering collaboration across functions, businesses can harness AI's full potential while mitigating associated risks. As companies navigate this rapidly changing landscape, success will depend on their ability to strategically leverage technology to create genuine value and maintain a competitive edge in an increasingly dynamic market environment.
About the Author
Heather Holst-Knudsen is a distinguished figure and expert in the events, media, marketing and technology sectors. Using her extensive experience, she guides clients in adapting to structural economic and market changes, seizing the chance to innovate and evolve. She specializes in digital and data disruption and opportunity, exploring how these overarching factors can impact revenue growth, customer-centricity, operational efficiency, profit margins, and the overall valuation of companies in both public and private markets.
Her journey began at her family business, Thomas Publishing Company, where she honed her skills. She further expanded her expertise by holding positions at early industry giants Miller Freeman, Reed Elsevier, and IDG. Returning to Thomas Publishing, Heather founded and spearheaded Manufacturing Enterprise Communications, an integrated media portfolio connecting buyers and sellers in the manufacturing and technology sectors. Starting in 2015 and spanning the next seven years, she leveraged her expertise as a revenue and business leader in various SaaS businesses, including Feathr, Gleanin, Brella and Edflex.
Heather is deeply passionate about digital innovation, data monetization, and AI and how these strategies fuel revenue growth, profitability, and company valuation. To serve and create value for clients in these areas, she launched H2K Labs, dedicated to generating and leveraging value through data for media, business information, events, and adjacent technology and service markets.
