AI trends for US equity investors

Interviews were held with a former executive at Intercom, divisional leader at Microsoft, and director at a US-headquartered pharmaceutical and biotechnology company. Third Bridge Forum is part of Third Bridge’s integrated research offering that also includes Community, Maps, and Primers and Tearsheets.

Conversation AI – Enterprise Chatbots & Customer Service Software – Emerging Generative AI Solutions & Potential Impacts – Former executive at Intercom 

• A former executive at Intercom believes ChatGPT’s release was “an iPhone type of moment”, with revolutionary AI models. In their view, AI investments should be focused on whether a company adds value on top of core ChatGPT infrastructure, building a durable and structural advantage.
• Customer support, marketing and sales will be the first segments to be transformed by AI. The expert added that regular users will notice significant ChatGPT improvements every 3-6 months, while people in the space will notice improvements weekly. Click here for a recent Third Bridge Forum report on ChatGPT.

AI in the Cybersecurity Industry – Use Cases & Innovation Outlook – Sector Update– Divisional leader at Microsoft  

• In an Interview looking at AI developments in cybersecurity, a divisional leader at Microsoft highlighted vulnerability management, detection and response as a key segment that is positioned for disruption.
• The expert said cloud vendors with sufficient scale, such as Google and AWS, are “in a unique position” to leverage AI in cybersecurity and consolidate solutions at an attractive price point given the rising cost of talent and challenges related to interoperability across the technology stack.
• Newer cybersecurity entrants face challenges for developing sophisticated AI, including high talent costs, building and designing systems, and hardware costs. While many training models are largely open source, access to high-quality data remains a key advantage for long-standing vendors vs newer entrants.

AI & Machine Learning in Drug Discovery & Development – Market Update & Transformative Potential – Director at a US-headquartered pharmaceutical and biotechnology company

• Turning to the drug discovery space, a director at a US-headquartered pharmaceutical and biotechnology company said AI improves drug discovery by optimising drug properties, predicting clinical trial success and extracting insights from scientific literature to shorten the costly and lengthy process of getting drugs to patients.
• The Interview also suggested that different algorithms have trade-offs between interpretability and predictiveness. In some cases, less powerful models with more interpretability may be better. Understanding the role of data is crucial for accurate predictions, we were told.
• We also heard AI is being used in biologics discovery to optimise sequences, automate patent space analysis and improve stability. Biologics are catching up with small molecules in terms of available data.
• The specialist said pharmaceutical companies initially collaborated with AI players, but many partnerships fell apart. Now, the former are building their own internal AI capabilities and forming relationships with niche AI companies.