New AI solutions and business innovations are emerging daily and can help companies work faster. However, thoughtful implementation of the right AI solutions can enable an organization to get its product to market more quickly. Startups and small-to-mid-sized businesses can use AI to offset limited resources when building products.

In this blog, let us understand how Gen AI can be harnessed for better product management.

The Benefits of AI in Product Management

From speeding up the Product Development Lifecycle (PDLC) to analyzing data at scale, deploying AI solutions offers various advantages for an organization’s business. A 2022 study from Deloitte on AI transformation found that 94% of Product Managers (PMs) agreed that AI is critical to success over the next five years, while 79% reported full-scale deployment of AI applications.

The following are the key benefits AI offers in product management:

• Efficiency: Drives greater efficiency in product development, enabling startups to do more with less. For example, AI technologies automate tedious tasks, freeing team members to concentrate on more important tasks.
• Speed: Helps teams work faster, accelerating time-to-market. Every second counts in a tech environment where competition is fierce and raising venture capital is more challenging.
• Data-driven decisions: Provides an organization with data insights to offer help in product decisions. AI and Machine Learning (ML) tools can analyze data and reveal trends and patterns at scale, often more efficiently than humans.
• Scalability: Enables startups to scale crucial processes that might otherwise require large teams.

The Impact of Gen AI on Product Management Tasks

Gen AI is expected to reshape the role of PMs substantially. The technology can expand Product Managers’ (PMs’) roles and responsibilities and fundamentally rewire the PDLC to achieve better customer outcomes in a shorter timeline. Given how new the technology is and how rapidly it is evolving, most product leaders are not sure about the tools to select, the use cases to start with, and how to help PMs make the most of Gen AI opportunities while adapting ways of working. However, the following conclusions can be drawn on assessing the impact of Gen AI on product management.

Faster Time to Market

PMs who used Gen AI tools (either generic tools such as ChatGPT or task-specific tools) took less time, to complete tasks resulting in faster time to market, by about 5 percent across a six-month PDLC. The time savings were because of the use of Gen AI to optimize user research, draft press releases in the discovery phase; create product one-pagers, write product requirement documents, and create product backlogs in the build phase. Thus, the adoption of Gen AI tools allows PMs to concentrate on more strategic activities, such as developing a long-term road map, defining the product vision, and conducting customer-facing activities.

Significant Uplift in PM Experience

Most PMs’ report an improvement in their activity experience when using Gen AI tools The tools are helpful with the tasks and PMs in general perceive Gen AI tools as automating their “high toil” tasks and enabling them to focus on what matters.

Increased Productivity

Gen AI tools have almost twice as much positive impact on content-heavy tasks, that is gathering and optimizing information, creating and polishing content, and brainstorming as compared to content-light tasks such as data gathering and visualization. This could be because content-heavy tasks have more potential for automation and because Gen AI is great at extracting insights from unstructured data and outperforming human content generation. In other words, content-heavy tasks inherently possess greater opportunities to harness the full capability of Gen AI.

Moreover, PMs tend to adopt more general-purpose tools such as ChatGPT than task-specific tools, and this results in about twice the productivity gains. This result is attributed to the fact that general tools are more familiar to PMs and thus easier to use than specialized tools.

Better Quality of Deliverables

Observation of the PMs and review of their deliverables suggest that on average, Gen AI tools enable them to iterate faster and create more accurate and complete output. However, the impact of Gen AI varies based on the experience levels of PM using them. PMs with more years of experience maintain a high quality of output, whereas more PMs gain productivity which could be at the expense of quality.

How to Approach AI Cautiously in Your Product Organization

While AI unlocks benefits, it also carries potential risks. Awareness of these downfalls and mitigating them in product development is critical to using AI responsibility.

Here are five ways product organizations can approach AI cautiously:

• Think of user privacy. Assess how your AI tools may impact security and user data privacy. Perform due diligence on providers’ protections and policies.
• Remember that AI models can give false correlations. Thus, you must validate insights with human oversight and triple-check any research or insights generated by a language learning model.
• Evaluate evolving regulations. Stay informed of emerging regulations governing the use of AI that may impact the organization and product.
• Maintain human involvement: We recommend that your employees be involved in reviewing and validating the inputs generated by AI.

Ways to Use AI in Product Management in Your Organization

As the AI space continues to evolve, we will see many use cases for teams to build better products more quickly. Following are a few ways to use AI within product management in your organization:

Developing Product Vision and Strategy

Planning and setting the strategy and product is a crucial first step for product managers before they begin executing. Defining the strategic direction streamlines the entire organization and this is where AI can help.

• Market analysis tools can quickly process data to display insights about market opportunities.
• Vision mapping tools can optimize research and inputs to create strategy documents.
• Design tools can quickly prototype concepts to better convey product and feature ideas.

Conducting Market and Competitive Research

As a product manager, you need to make strategic decisions. However, compiling data on competitors—their pricing and product specs as well as analyzing market trends is time-consuming. AI tools can automate these processes.

• Web scrapers can rapidly collate the pricing, features, and other data from competitor websites.
• Sentiment analysis tools can digest customer feedback on competitors at scale to surface strengths and weaknesses.
• Market research assistants can create detailed market analysis reports using natural language capabilities.

 Defining Product Requirements

Clearly defining specifications and product requirements is crucial for success. However, compiling all the inputs and translating them into detailed docs is a tedious job. AI can help enhance and streamline the requirements process in several ways:

• Analyze customer research data to automatically tag key needs and extract requirements.
• Writing assistants can take product briefs and create detailed technical specifications.
• Quickly synthesize cross-functional stakeholder feedback to build consolidated requirement docs.

Prioritizing Features on Your Product Roadmap

One of product management’s most critical and challenging aspects is to determine the features to prioritize and include in upcoming releases. AI can introduce objectivity into feature prioritization and roadmap planning.

• Score and rank potential features based on different inputs like customer requests, revenue potential, or cost.
• Sentiment analysis provides a good amount of data on customers’ feelings about potential features, scouring social media and other data sets for insights.
• Predictive AI modeling can forecast the business impact of features to inform prioritization.

Managing Product Launches

Successful product launches require extensive cross-functional coordination and management of complex details—development to marketing activities. AI can help automate sections of launch management to enhance efficiency.

• AI assistants can develop comprehensive launch plans to keep all activities on track.
• Scheduling tools can optimize launch timelines and marketing campaign activities as progress is tracked.
• Generative AI writing tools can help create a marketing collateral, instead of having to write it from scratch.

Conclusion

In conclusion, AI technology in product management can transform the way products are managed and developed. By leveraging the power of AI, product managers can gain valuable insights from user feedback, improve meeting efficiency, and automate product specification creation to gain a competitive advantage in the market.

Get in touch with Aretove to enhance product management by leveraging AI to drive smarter, data-informed decisions, automate time-consuming tasks, and gain better insights into customer behavior and market trends. From optimizing product roadmaps and pricing strategies to delivering personalized user experiences Aretove’s AI solutions empower product managers to be more agile, efficient, and customer-centric. Aretove helps organizations not only streamline operations but also innovate and stay ahead in a competitive market.