Introduction
AI product management is an ever-growing industry that can boost the career growth and improvement for working professionals and freshers. Having sound knowledge of artificial intelligence practices in managing the product lifecycle and building AI-powered systems that resolve mundane challenges are some of the core pre-requisites to being a successful AI product manager.
However, contrary to popular misconception, an AI Product Manager (AIPM) need not know everything about coding or learn multiple coding languages. They need to understand the nuances of the implementation and assist the team in ensuring a successful implementation in the best possible way. The key here is to understand the business, keep tabs on the client’s requirements, and suggest suitable methods that can help in optimizing operations in the best possible way.
AI-driven Product Planning and Prioritization
As an AIPM, you need to look at the choices that successful organizations have made in deploying their AI product plan. Once you are done, you need to set AI ambitions that implement a strategic impact that aligns with the business strategy. The strategy that you plan needs to align with the organization's business objectives and overall goals. You need to ensure the following while implementing a strategy for the AI roadmap.
- ● The initial AI strategy should inform the adoption goals for the roadmap and the priorities for the use-case portfolio.
- ● Establish a process to refine the strategy.
- ● Realizing the value of AI via a portfolio of initiatives and building an AI strategy. ,li
- ● Prioritizing initial use cases, running pilots, and demonstrating business value.
- ● Create a portfolio of AI products and models that are aimed at ongoing value creation and can evolve with customer requirements and changing technology (building a value proposition for business growth).
Start with a Use Case and Perform an Audit
As an AIPM who is new to an organization, the senior management and stakeholders will not trust you right off the bat. The best way to establish trust is by first analyzing the current processes followed by the organization and, most importantly, looking for areas where AI is being deployed. The next step would be to perform an AI audit of the important operations and suggest ways to optimize the process. You need to work on the following objectives while performing the audit.
- ● Take stock of your existing tool stock and the data collected
- ● Consider whether you have access to usage metrics and support tickets
- ● Also, check whether the systems are integrated or siloed
- ● Perfect data is not required to begin; however, understanding the baseline will guide your approach
The AI roadmap process needs to be framed in a manner where AI can add immediate value by consolidating customer feedback and analyzing product usage patterns as well. A pro tip would be to choose an attribute that can be measured and contained, as it will help in demonstrating early wins and build trust with stakeholders easily.
Choose Tools that can be Integrated and are Scalable
With the current technology and AI capabilities constantly evolving, companies are looking to implement platforms that offer out-of-the-box AI capabilities that blend with the existing ecosystem. For example, you can use tools like Productboard Pulse to help you surface and prioritize customer insights. Leading corporations and IT companies like to keep their data layer enriched with behavior analytics like Amplitude and Mixpanel Enrich.
Using tools which are not scalable and are based on the legacy architecture is an absolute waste, as it has limited options for AI integration and could be a liability for the business in the future. Also, it is essential to conduct a periodic audit of the AI systems and implement continuous upgrades whenever required. Even if a particular field is beyond the scope of work or KRA, it would be ideal for you to audit that area as well. This will help you stay in good standing and land you a promotion in your job.
Engage Human Intervention at Every Touchpoint
Although AI systems have grown phenomenally over the past few years, it is essential for AIPMs not to completely rely on the system to run operations. AI must never override human judgment and requirements. You need to establish checkpoints that managers can review, make adjustments, and override AI-generated insights whenever required. This ensures that the entire team is in control of the technology, ensuring that all processes are driven at the right moment and the right time. Having control of the AI system’s potential and overall capabilities will always help you keep your systems in check.
As an AIPM, you can use natural language generation and describe your roadmap more efficiently. Use AI to simplify the roadmap creation process to speed up the process, implement resource availability, and look into potential risks which can amplify potential risks. Look to implement machine learning models that sketch a timeline that aligns with the project goals efficiently. You could also use an AI product roadmap generator to assist you in the process of generating a roadmap.
Establish Cross-Functional Collaboration
Integrating AI systems with cross functional teams, including the stakeholders, is essential for you to fit into the broader product strategy. This is because it will help in improving decision making by establishing transparency and make the process more visible across all the touch points of the implementation. By keeping the stakeholders in the loop, you not only increase the probability of the project receiving more traction in the organization but also ensure that the company gets more funding, along with valuable ideas that can enhance the existing system. One pro tip is to integrate AI with all team collaboration activities so that all employees are updated with the roadmap strategy. Also, AI can help by providing essential ideas which help you structure presentations and assist by creating visual elements.
Managing Risks and Overcoming Challenges
AI can also pose a couple of risks and biases that could jeopardize the entire project. As an AIPM, you need to look at the biases in AI algorithms that could impact real-world applications. You can overcome this by evaluating AI-generated outputs and implementing them into the decision-making process in a thoughtful and efficient manner. The key is to strike the right balance between using AI’s potential to ensure ethical and responsible usage. Always use AI as an assistant and not a replacement.
Managing critical AI-related activities into separate workstreams that enable leaders to choose the right attributes that suit AI’s ambitions. Sequencing the details into separate workstreams from initial to the most advanced operations helps in seamless execution.
Building an AI product roadmap could be quite challenging as it involves a lot of planning, research, and alignment with business objectives. You could also face challenges in using the right AI product roadmap tools and managing resources effectively. That’s where Eduinx will help you with a personalized touch to learning AI product management course.. With a team of mentors who have over 10 years of experience in AI, you will get hands-on training on the best practices in crafting the perfect AI roadmap for efficient product management. Eduinx also provides 360-degree career support and placement assistance for you.
Reference links:
https://productschool.com/blog/artificial-intelligence/10-ideas-to-build-an-ai-driven-roadmap https://www.gartner.com/en/articles/ai-roadmap https://www.productboard.com/blog/using-ai-for-product-roadmap-prioritization
