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92% of product managers predict a lasting impact of AI on product management, finds study

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impact of AI

The advent of artificial intelligence (AI) has revolutionized industries across the globe, prompting a significant shift in product development and management practices. As organizations strive to stay ahead in a rapidly evolving marketplace, understanding the impact of AI on product management becomes crucial.

According to a recent report by airfocus, an overwhelming majority (92%) of product managers believe that AI will have a lasting impact on product management.

Malte Scholz, CEO and CPO at airfocus, says, “In 2023 PMs will be thinking about ways how to incorporate different AI models into their products to not be left behind.”

These professionals envision AI contributing to improvements in workflow efficiency (84%), product discovery (43%), and data analysis (33%), among other areas. With such promising prospects, product organizations need to comprehend and embrace the potential of AI.

impact of AI on product management

Consequences of not adopting AI

According to respondents, the areas of product management that are expected to be most influenced by AI include market research and user research (68%), idea management and feedback collection (50%), technical specifications and requirement documents (49%), product discovery techniques (37%), product development and release planning (31%), roadmapping and strategizing (28%), and prioritization (25%).

The failure to integrate AI into product management practices can have severe repercussions. Neglecting AI adoption may result in diminished competitive advantage, as organizations risk falling behind competitors who leverage AI to streamline operations, make data-informed decisions, and anticipate consumer behavior effectively.

Furthermore, operational inefficiencies may arise due to missed opportunities to automate routine tasks and optimize workflows, hindering overall productivity and growth.

Impaired decision-making is another critical concern without the support of AI-powered tools. Companies may struggle to analyze vast amounts of data accurately, leading to intuition-based decisions that may be less reliable.

Additionally, customer satisfaction could decline if organizations cannot meet the evolving expectations of personalized experiences that AI can facilitate. Stifled innovation is yet another consequence, as companies may find it challenging to balance innovation with limited resources in a rapidly changing market.

Overcoming challenges and implementing AI strategies for success

When implementing AI in product management processes, certain challenges commonly arise. Among respondents who faced obstacles, the most prevalent issues included generating reliable and valuable outputs (20%), obtaining internal buy-in and fostering adoption (19%), addressing data security and regulatory concerns (16%), acquiring the necessary knowledge and skills (16%), and defining clear use cases and return on investment (12%), among others.

To overcome these challenges, here are seven strategies for implementing AI successfully:

  1. Identify clear use cases and potential ROI: Articulate the specific areas where AI can add value and estimate the return on investment for these use cases.
  2. Focus on training and skill acquisition: Invest in upskilling existing staff, hiring new talent with AI expertise, or partnering with external consultants or solution providers to foster AI knowledge within the organization.
  3. Leverage existing AI solutions: Rather than building AI capabilities from scratch, explore and integrate existing AI solutions that align with your product management processes, ensuring quicker and cost-effective implementation.
  4. Prioritize data security and compliance: Allocate resources to address data security and regulatory concerns, invest in secure AI solutions, conduct thorough risk assessments, and ensure compliance with data protection regulations.
  5. Phased integration into product development: Adopt a long-term strategy by integrating AI into your product or service offering in phases, starting with small beta features that require minimal investment to develop and test.
  6. Promote internal buy-in: Garner support for AI adoption by demonstrating its potential benefits, showcasing successful use cases, building a business case, and involving stakeholders throughout the implementation process.
  7. Build internal AI resources: Consider creating dedicated AI teams or centers of excellence, or invest in infrastructure to support AI utilization, thereby maximizing the organization’s AI capabilities.

As the business landscape evolves, AI has emerged as a game-changer for product organizations. Embracing AI is not just a trend but a necessity for those seeking to stay competitive and drive innovation. By effectively leveraging AI, product managers can enhance their capabilities, focus on critical areas, and deliver exceptional value to customers. Embracing a proactive approach to AI implementation, fostering a culture of continuous learning, and encouraging collaboration will be key to thriving in the dynamic world of product management.

Source: airfocus

Read next: Top 10 AI trends in 2023 that CIOs should know

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