About the Author
Seema Sodhani
Seema Sodhani is a Product Strategy & Marketing leader with in-depth experience in the health technology and biotech market. Seema has achieved a successful track record of building and launching health tech SaaS and application offerings. She brings a sophisticated product strategy, design, and brand development process to c-suite and product/marketing leaders.
Five simple steps a product manager can take to incorporate AI into their Healthtech SaaS product roadmap:
- Identify Use Cases: Start by identifying specific use cases where AI can add value. Consider areas such as predictive analytics using machine learning or simply automating manual processes. Determine how AI can enhance user experience, improve efficiency, or deliver better outcomes. Healthtech experts like Seema Sodhani can help your teams brainstorm not only the use cases, but also the ones that would be most commercially viable.
- Market Validation: Understand if your customers are ready to accept new ideas that might have felt impossible before. Sometimes our customers have not caught up to unleashing the power of AI and may not trust the outputs.
- Conduct a Feasibility Assessment: Evaluate the technical feasibility and readiness of implementing AI within your product roadmap. Assess the availability of data, required infrastructure, and any potential constraints or limitations. Determine if you have the necessary expertise in-house or if you need to collaborate with AI specialists or data scientists.
- Prioritize AI Features: Prioritize the AI features or enhancements that align with your product roadmap and customer needs. Consider the potential impact, value, and feasibility of each feature. Start with smaller, achievable AI initiatives and gradually expand as you gain more experience and confidence.
- Data Acquisition and Preparation: AI relies on quality data for training and making accurate predictions. Ensure you have access to relevant and clean data sources for your AI initiatives. Unstructured data sets like electronic health records (EHR) will need to go through a structured process before use. Develop a data acquisition and preparation plan to collect, clean, and organize the data in a format suitable for AI model development.
- Iterative Development and Evaluation: Adopt an iterative approach to develop and integrate AI features into your Healthtech SaaS product roadmap. Collaborate closely with AI experts, data scientists, and development teams to build, train, and refine AI models. Continuously evaluate the performance, accuracy, and user feedback to improve and iterate on the AI features over time.
Remember to document and communicate the progress and impact of incorporating AI into your Healthtech SaaS product roadmap. Regularly assess and refine your AI initiatives based on user feedback, market trends, and competitive landscape. This will help you unlock the potential of AI and keep you ahead of the competition in this dynamic industry.
* This blog post originally appeared on RIVIR’s blog.
