5 reasons to leverage a PM for AI-powered products.
The unprecedented near-ubiquity of AI tooling lends itself to multiple usecases for your business. The unique challenges to go from concept to product for AI-driven products are fraught with complexities that an experienced AI-PM is best positioned to navigate.
AI product managers are the brains behind the bots, turning data into decisions and code into cash!
AI-driven products leverage artificial intelligence (AI) technologies to provide enhanced functionality, automation, and predictive insights. These products use various AI techniques such as machine learning, natural language processing, computer vision, and robotics to perform tasks that typically require human intelligence. Applications can really range the gamut, from virtual assistants (Google assistant, Siri), recommendation engines (think your Netflix queue), autonomous vehicles (Tesla autopilot, Waymo), chatbots, healthcare diagnostics, fraud detection systems (banking or cyber security), predictive maintenance, personalization engines (mobile news, Amazon's shopping page), image/video analysis and smart home systems. This is definitely not a comprehensive list, but I want to emphasize the diversity of applications and where a product manager really shines due to this diversity of needs.
1. Buy-in from technical and business stakeholders
AI projects often involve multidisciplinary teams, including data scientists, engineers, systems architects, and business stakeholders. An AI PM's role is to be the glue between these groups. They use their technical expertise to craft compelling functional requirements and oversee testing and deployment strategies. They are intimately understand the nuances of AI algorithms, data requirements, and model training processes. Simultaneously, they articulate the business value of AI features to non-technical stakeholders, ensuring alignment with organizational goals.
2. Managing data as a strategic asset
An AI PM must understand the importance of data quality, availability, and security. They work closely with data engineers to establish robust data pipelines, ensuring that the AI models are trained on clean, relevant, and diverse datasets. They oversee data governance to maintain compliance with privacy regulations. Finally, they recognize the importance of the flywheel of data - feedback for continuous improvement of the AI model and build Customer features to ensure the flywheel.
3. Ethical AI to build Customer trust
Ensuring that AI products minimize bias and bolster fairness are key to ensuring continued Customer trust. An AI PM finds features and UX mechanisms to build in transparency in the AI product's development processes. Additionally, they ensure that AI solutions comply with legal and regulatory standards, fostering trust among users and stakeholders.
4. Go-to-market quicker
Building a standalone AI model is only 1/2 the battle; integrating it into the product is equally important. An AI PM manages dependencies, resolves technical bottlenecks, and ensures that the final product delivers a cohesive user experience. Their technical acumen allows them to anticipate potential challenges and devise strategies to address them proactively.
5. Test, Optimize, Iterate
An AI PM builds product mechanisms to encourage experimentation and innovation. They build forward facing roadmaps for feature enhancements and new product ideas by staying abreast of AI trends and your Customer's needs. They facilitate A/B testing to optimize user flows and maximize Customer conversion.
6. An asset to your SR&ED claim
Last, but certainly not lease, an AI PM can be an invaluable asset to your SR&ED claim by ensuring that your development documentation is spotless. This is leveraged to capture all details of your R&D work and creates a retrospective record of time spent by all collaborators on R&D activities.