This article explores AI’s profound impact through two critical lenses: leveraging it for efficiency and productivity and for product innovation. This dual approach is vital for transforming how we build, deliver, and evolve software and business operations today.

But how do teams truly navigate this rapidly evolving landscape? What does it mean for individuals and functions to embrace AI? AI is transforming how engineering and non-engineering teams work, make decisions, and create value. Achieving this demands a mindset where every team, regardless of function, actively seeks to integrate AI into their daily operations and collaborate on tailored solutions.

Below I explore each area of impact by outlining the shift ‘From’ traditional approaches ‘To’ AI-driven strategies, highlighting the ‘Focus & Mindset’ required for success.

The Dual Impact of AI

From: Leveraging AI to make processes faster.

To: Leveraging AI to enhance both process efficiency and product intelligence & value.

Focus & mindset change required: Recognize AI as a strategic asset for both internal operations and external product offerings. Leverage efficiency and integrate it with a strong focus on value creation.

Optimizing the Software Development Lifecycle (SDLC)

From: Manual, siloed, and repetitive software development.

To: An SDLC intelligently enhanced by AI tools for:

• AI-assisted coding
• AI-powered testing & QA automation
• AI-enhanced UX/UI design
• AI specialized pod team structures

Focus & mindset change required: Embrace AI as a co-pilot. Consider forming specialized AI “pod” teams from the outset. These multidisciplinary teams, comprising AI experts alongside engineers, designers, and domain specialists, can embed AI thinking and capabilities throughout the entire development process from the start. Encourage engineers to expand into full-stack thinking and proactively integrate AI tools into every sprint. Establish AI-focused pods from project inception.

Driving Product Innovation & Value (Human in the loop)

From: Blindly adopting AI for the sake of it. Feature-first or hype-driven AI usage

To: Problem-first, user-centric AI integration that:

• Genuinely solves user problems with human-centric design.
• Adds tangible, measurable value.
• Creates truly innovative, ethically sound AI-powered solutions.

Focus & mindset change required: Prioritize problem definition and human impact before technology. Develop an approach, where AI serves human needs at the forefront. Essentially, embrace the “human in the loop” philosophy, where AI supports, not replaces, human judgment and empathy.

Elevating and Redefining Customer Partnerships

From: Simply delivering technology solutions and transactional client interactions.

To: Co-innovation with clients, including:

• Deeply understanding evolving strategic goals.
• Collaborative PoCs using current and emerging AI tools
• Deliver value as forward-thinking advisors.
• Integrate AI performance metrics with user experience metrics

Focus & mindset change required: Every interaction is a continuous opportunity to build trust as tech-savvy partners. This demands active listening, genuine empathy for client needs in a dynamic environment. Be a tech-forward partner. Use every interaction to educate, validate, and evolve client expectations of what AI can achieve.

Unlocking AI-driven workflows

From: Operating within function-specific silos and relying on traditional tools.

To: Proactively using current & emerging AI to:

• Transform daily operations for efficiency and strategic insights.
• Collaborate with technical teams to integrate AI solutions that are tailored to departmental needs.
• Cultivate AI-ready organizational culture across all functions.

Focus & mindset change required: Build data literacy and AI fluency across all functions. Integrate new AI tools into daily workflows. Partner with technical experts to implement and refine these solutions. Ignite widespread AI adoption and ideation, host regular “AI-thons” for both tech and non-tech teams. You would be amazed to see how the ideation happens within diverse teams.

Adapting AI Across Experience Levels

From: A “one-size-fits-all” enablement

To: Audience-specific AI upskilling:

• Gen Z: Are digital natives. Build on digital fluency for current & future AI
• Middle Generation: Leverage architectural and domain expertise with AI for complex problem-solving.
• Seniors: Champion AI adoption, responsible AI, steer strategy, be thought leaders and navigators of organizational AI transformation.

Focus & mindset change required: Nurture an inclusive learning environment where every generation feels empowered and valued in their AI journeys. Promote cross-generational knowledge sharing and mentorship to leverage diverse perspectives. 

Embracing evolution, self, and AI

From: Fear of AI disruption

To: Embracing AI as a partner for growth and transformation

• Embrace change: AI is evolving and so must we!
• Normalize ambiguity and cross-skill learning
• Encourage safe spaces for innovation and experimentation.
• Recognize AI’s strengths and weaknesses.

Focus & mindset change required: Develop a growth mindset that sees AI as an opportunity for augmentation and innovation. Evolve continuously—personally, technically, and organizationally.

Cultivating a data-driven experimentation & feedback loop

From: Static implementations.

To: Continuous data collection, A/B testing, and feedback-driven iteration for AI models and applications.

Focus & mindset change required:  Prioritize metrics, user feedback, and rapid iteration to optimize AI performance and user value. See experimentation failures as learning opportunities.

Concluding thoughts: From tool to transformation

From: Viewing AI as merely a tool.

To: AI as a force that reshapes how we think, collaborate, and deliver impact

Focus & mindset change required: Leverage the strength of human intellect amplified by AI’s evolution. Empower every individual and team to become AI-native—where innovation and efficiency are inseparable.

Neurealm Labs: An AI-first approach to innovation

Neurealm Labs vividly exemplifies an “AI-first mindset” that actively shapes the innovation landscape and drives the development of cutting-edge solutions. This includes a strong emphasis on Generative AI for predictive intelligence tools like 3rdi, AI-powered solutions for healthcare efficiency, such as patient flow optimization and HAI risk prediction, and AI-driven passwordless authentication.

Author

Manisha Deshpande | VP, Digital Platform Engineering | Neurealm

Manisha brings over 25 years of experience in the IT industry and currently serves as the VP of Digital Platform Engineering at Neurealm. She advocates a design-led mindset and a human-centric approach to product development. Her expertise spans the entire product engineering lifecycle, with a current focus on digital modernization, mobile-first experiences, and leveraging AI to enhance engineering productivity and innovation.