Leveling-Up as a Product Manager in the Age of AI
Yesterday I gave a virtual presentation to 80 product managers from across the US, sponsored by the Boston Product Management Association (BPMA)..
The BPMA is a professional organization based in Boston, Massachusetts, focused on product management. BPMA provides a community and resources for individuals working in or interested in the field of product management. The association offers networking events, educational programs, workshops, and conferences to help product managers, professionals, and enthusiasts enhance their skills, share knowledge, and stay updated on industry trends. BPMA plays a pivotal role in connecting professionals, fostering collaboration, and promoting best practices in product management within the Boston area.
The following is a summary of the presentation:
The release of ChatGPT 3.5 in November 2022 has sparked an AI revolution on both mainstream and in the tech industry. Virtually overnight, AI capabilities have advanced tremendously. Businesses now have new opportunities to harness AI, but also new risks to manage.
Pre-ChatGPT 3.5, businesses relied on conventional computing with limited data-driven decision making. Lots of manual processes and human intervention were needed. Personalization and user experience were also limited.
Post-ChatGPT 3.5, there is an emphasis on AI-driven solutions, data-centric decision making, and automation for efficiency. Enhanced personalization and user experience are possible with AI. Companies can enable more tasks with AI across industries.
However, important new considerations are AI ethics, bias in coding and datasets, and responsible adoption. AI hallucinations have emerged an issue. (NB product managers) Job roles are shifting as AI integrates into new applications — especially personalized and vertical app’s, SaaS and data-centric projects and companies.
Product managers can level-up by getting fluent in AI fundamentals, using generative AI, brushing up technical skills, and focusing on problem solving. Understanding the AI ecosystem and blending AI knowledge with product management best practices is key. Most importantly: focus on developing a compelling AI vision.
Specializing in AI products involves strategizing where to incorporate AI, defining requirements with technical teams, managing costs and risks, overseeing AI product development, assessing model performance, building business cases, and educating customers. AI product managers connect AI capabilities to business goals to produce new and expanded customer value.
The AI revolution brings immense opportunities as well as risks. With responsible adoption, businesses can unlock new levels of efficiency, insight, and customer value with AI. The future is here.