ChatGPT and Artificial Intelligence (AI) are at the forefront of the majority of strategic discussions across the B2B SaaS and Cloud industry.
Paul Roetzer started as a journalist and then leveraged that writing expertise into founding a marketing agency. Due to the launch of Watson by IBM, Paul's curiosity about how AI could impact Marketing started his journey to becoming an industry expert in how B2B companies are and could leverage AI to increase the efficiency and effectiveness of Marketing. In 2016 Paul founded and launched the Marketing AI Institute within his agency, and then spun it off as a separate company in 2019.
How has the use of AI by B2B marketers changed over the past couple of years? Paul believes the inflection point started in the spring of 2021. First, Sam Altman - CEO of OpenAI/ChatGPT published the seminal article - Moore's Law for Everything. Then, Genius Makers, a book by Cade Metz, a writer for the New York Times was published.
Paul was confused why AI did not take off earlier in 2011 when AI teams at Google, Facebook, and Microsoft were first formed. He concludes that he overestimated how quickly AI would go mainstream and underestimated the impact it was going to have on the industry, the economy, and the world. The public release of ChatGPT was the catalytic moment for AI awareness to become mainstream.
Why has AI taken so long to be adopted by industry? Paul discusses hundreds of use cases that have been in place for 5+ years, around strategy and personalization. The challenge was the majority of marketing leaders did not know how to best leverage the power of AI, nor the accessibility which was still difficult to access, leverage, and exploit previous to the public release of ChatGPT.
In the Bessemer Venture Partners "State of the Cloud 2023" one of their 5 predictions is that the initial value of AI will accrue to the individual users not to the entire company. In the spring, of 2023 Paul wrote an article entitled " The law of uneven AI distribution". The perspective shared in the article is that until C-Level executives begin to understand the full value of AI they will not lead the adoption across their department. A second point is that access will need to be granted to employees as in many industries and regions of the world access is still limited. Paul's third point is that executives will need to understand the risk, reward, and investment trade-offs required before they will fully support a broad-based roll-out of AI across their companies - especially in regulated industries.
The "HOT TAKE" moment in the episode was at minute 12:40 when Paul shared that he believes many B2B SaaS companies will become obsolete quickly, It's hard to know what the "moats" are for many B2B SaaS providers beyond data and distribution. B2B SaaS organizations that have proprietary data to help tune generative, LLM-based models will have an unfair advantage, and a large customer base is best positioned to ride the AI wave and further differentiate and protect themselves from traditional B2B SaaS competitors.
A highly defensible moat is that the companies that have the most data to train and tune AI models, such as the 4 Billion+ miles of training data that Tesla has amassed over the last 10 years. Salesforce is a great example of a company with large datasets that could form the foundation for the highly defensible application of AI.
Paul believes that a B2B technology company that does not have a roadmap for AI, and resources to build or integrated into their core product will not be VC fundable in the future - if not already. The ability to quickly develop, deploy and refine AI-centric functionality will be table stakes for legacy Saas vendors or early-stage companies will be able to quickly eclipse incumbent vendors UNLESS they have applied AI to their data and distribution assets.
How do Marketers being to embrace and utilize AI for their department? First, in a problem-based model, Marketers need to identify those problems/challenges that are most prominent in their department, the benefits of solving those issues, and then assess if there is smarter "AI" technology to address the top challenges in a prioritized, rank order.
The second approach is to use a "task-based" approach and identify those activities their marketing team is executing daily, and how can AI increase their efficiency. Paul shared the 21-step process he uses to publish their podcast, how they use AI tools for half of the steps, and reduced time spent per episode from 15 - 20 hours to 3 -5 hours.
Paul's closing advice to early career professionals - raise your hand in your organization and take the lead on building or being a leader in an "AI Council" in your company. Simultaneously become a student of AI and specifically how it can be used to increase personal efficiency, and company effectiveness and create your position as a future leader for the company.
If you are a B2B Go-to-Market executive, work for a B2B GTM executive, or have B2B GTM executives work for you - listen to the conversation with Paul Roetzer, Founder and CEO at the Marketing AI Institute.