Discover how Generative AI (GenAI) is redefining how digital products are conceived, built, and experienced, driving growth and efficiency for organizations. Here are three key strategies product leaders can use to accelerate product development lifecycles with GenAI.
of surveyed organizations are investing in Generative AI¹
of surveyed organizations are increasing their investments in GenAI to achieve higher efficiency and productivity²
of surveyed organizations say they will scale 30% or less of their current experiments in the next 3-6 months³
GenAI is becoming an integral part of how we work, and there is ample opportunity to unlock its value for digital products. Not only is the GenAI market set to hit $200 billion by 2032⁴, but 67% of organizations are already increasing their investments in GenAI to achieve higher efficiency and productivity.² GenAI is poised to turbocharge the adoption of digital products, defined as any good, service, or experience that is created, distributed, and consumed through digital channels to fulfill customer needs and create value for organizations.
Despite increasing expectations for transformational impact, only 38% of surveyed organizations deploying GenAI track productivity improvements.² Hence, the quest to realize value from GenAI is at the center of product organizations' strategic agendas. Based on proprietary market research and experience in enabling product organizations to leverage GenAI's value, we have identified three key success factors driving GenAI value realization.
To realize the value of GenAI and maximize its impact, product organizations should:
1. Define the strategic ambition and aspiration of GenAI
While 90% of organizations are investing in GenAI¹ and 67% are increasing their investments², some organizations fail to realize full value, more than two-thirds of organizations will scale 30% or less of their current experiments in the next three to six months.³ The initial step for an effective strategy is to clearly articulate your desired outcome and its winning aspiration. Leading product organizations know what they want GenAI to enable for the organization, and they are tracking how it adds value.
2. Design GenAI-enhanced digital products with consumers at the center
Based on a survey and ethnographic research involving over 1,000 US adults, we identified four dominant consumer mindsets toward GenAI: “the Optimists,” “the Maybes,” “the Unaware,” and “the Avoidants.” Although they have various preferences, concerns, and perspectives around GenAI, 80% are open to trying GenAI-enhanced digital products and experiences.
Designing GenAI-enhanced digital products that meet the needs of these mindsets relies on three guiding practices:
Our findings suggest that leading product organizations applying these core principles achieve higher top-line performance (revenue growth, retention, etc.) than their industry peers.
Read more about how GenAI mindsets matter and the design principles that can help create trustworthy digital products for consumers at scale.
3. Apply GenAI across the product lifecycle and train product teams to use GenAI tools effectively
Leading product organizations apply GenAI across the product lifecycle to boost creativity and maximize operational efficiencies. The product lifecycle journey below outlines use cases of how some are applying GenAI to maximize its impact.
GenAI + digital product development use cases
There are many ways to leverage GenAI across the end-to-end digital product development process.
DEFINE
Research synthesis: Conduct and summarize research to identify customer needs, competitor positioning, and growth opportunities
Automated requirements gathering: Streamline and enhance the requirements gathering process with AI-driven automation
Production roadmap creation: Create strategic and data-driven product roadmaps for development planning
DESIGN
User interface (UI) design editing: Assist in editing and refining UI designs for optimal user experiences
User experience (UX) analysis: Assist in analysing and optimizing user experiences for digital product enhancements
Wireframe creation: Support wireframe creation with automated suggestions for efficient design planning
BUILD
Automated code generation: Accelerated development with AI-generated code segments for efficiency and reduced manual coding
Code documentation: Automated generation of code documentation for improved clarity and understanding in development projects
Code review and analysis: Assist in code review processes, identifying issues, and ensuring code quality
TEST
Automated 3P integration: Automate updates and maintenance for seamless third-party integrations in digital products
Automated A/B testing: Automate A/B testing for rapid and data-driven optimization of digital product variations
Test case generation: Automate the generation of test cases for comprehensive testing coverage
LAUNCH
Concept validation: Validate product concepts with AI-driven analysis and feedback for informed decision-making
Personalized onboarding: Personalized onboarding experiences for improved user engagement and understanding
MANAGE
Automated error data management: Automate the identification, tracking, and magement of errors in digital products
GenAI bug detection: Detect and identify bugs for efficient debugging in digital product development
ITERATE
Product feature attribution: Analyze and attribute the impact of product features for infomred development decisions
Rapid prototyping: Accelerate product updates with AI-driven rapid prototyping for quick concept valitaion
GenAI benefits, by the numbers
of developers say GenAI tools give them an advantage, from better code quality to faster completion⁵
cost savings reported by survey respondents (4.6% through reduction in headcount)⁶
improvement in productivity reported by survey respondents⁶
How to maximize the value of GenAI
Although GenAI can be well applied across the entire product lifecycle, we believe product organizations can maximize value by focusing on three key areas:
Today, design iteration and prototyping can be time-consuming.
GenAI can assist in developing new prototypes and products. This can help prompt creative thinking, aid rapid prototyping and iterative testing, and optimize experiences to generate designs efficiently and at pace.
“There are three real buckets where we think generative AI will make a difference. Productivity is bucket one. The second is user experience—the interaction between users and the product. And the third is customer experience, how our customers interact with us as a company. Those three areas are where I think generative AI stands to make some pretty big functional differences.” 7
– Mahesh Saptharishi, executive vice president and chief technology officer, Motorola Solutions
Today, developers are challenged with the accuracy of complex coding and debugging.
GenAI can support software developers by creating and maintaining code, particularly for repetitive tasks. This enhances efficiency and helps ensure code consistency, freeing them up to focus on higher-level tasks such as complex code writing.
"Gen AI coding tools are often seen as more like autocorrect: a tool that is used dozens of times per day and enhances productivity by roughly 10 to 20 minutes per day.” 8
3. TEST
Today, testing and issue resolution is resource intensive.
GenAI can help test the code and usability of digital products by generating test cases and identifying bugs and improvements, ultimately saving time and increasing speed to market.
"Gen AI tools for writing and testing software appear to be among the most compelling and user-ready use cases for enterprise adoption in tech companies.” 8
Assessing the impact of GenAI across the digital product lifecycle of multiple organizations, we found compelling evidence of its substantial business value. Digital organizations applying GenAI across their lifecycle improved speed to market resulting in time saved across areas such as product management, engineering, and quality assurance.
To fully maximize the adoption and value of GenAI across the product lifecycle, product leaders also need to train their product teams on using GenAI tools effectively. Leading product organizations training their workforce achieve more than 40% higher adoption.⁹ However, only 38% of organizations provide GenAI trainings to their workforce. Hence, bringing the workforce along with the transformation is critical to yielding the value of GenAI in digital product fully.
By applying GenAI along the product lifecycle and training product teams on GenAI proficiency, leading product organizations can achieve higher creativity, efficiency, and productivity.
About the authors
Tim Juravich is a principal at Deloitte Digital and co-leads our Product Innovation practice. Tim and his team bring industry-leading design, product management, and experience engineering capabilities to our clients to launch digital experiences that move people and spark growth in web, mobile, and emerging technologies.
Courtney Sherman is a principal at Deloitte Digital and co-leads our Product Innovation practice. As an expert in human-centered design, she develops solutions that cross over the physical and digital environments, including innovation strategy, customer experience strategy, concept development, and innovation capability building.
Menes Etingue Kum is a senior manager at Deloitte Digital, in our Digital Product and Innovation practice, where he helps financial service companies define and execute on innovation strategies that elevate the human experience.
Chris Sommerfeld is a principal at Deloitte Digital, leading our Digital Product Strategy & Design team. He works closely with clients to design, build and launch compelling digital experiences as well as to enhance their digital product capabilities.
Anthony Jardim, Jenny Kelly, Christine Kang, Sara Ciaramella, Karen Escarcha, Mariel Soto Reyes, Victoria Estacio, and Jasmine Oo also contributed to this research.
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Mindsets matter: Four keys to creating GenAI experiences consumers trust
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8. Deloitte, Tech companies lead the way on generative AI: Does code deserve the credit?, 2024, https://www2.deloitte.com/us/en/insights/industry/technology/gen-ai-coding-tools.html#endnote-6, accessed March 7, 2025.
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