Why companies should shift towards a customer-centric AI strategy

In pursuing digital transformation, businesses realize the importance of customer-centricity. Each customer interaction is a chance to offer unique, excellent experiences that improve business results and revenue. Customer-centricity should be integral to a company's culture and operations, guiding business, and technology strategies. With AI, the ability to provide hyper-personalization further amplifies customer experience. Thus, the main digital strategy should revolve around customer focus and innovation, leading to enhanced value. 
Product-centric operations enabled by a platform ecosystem 

Recognizing the need for embedding customer centricity in their DNA, enterprises are shifting their approach towards innovation and value assessment, adopting a product-thinking mindset that prioritizes experimentation and co-creation. Furthermore, they are increasingly leveraging the platform ecosystem to drive collaboration and growth.

While enterprises have embraced Agile, DevOps, and SRE for speedier time-to-market and responsiveness, only a handful have regularly achieved superior customer experiences, brand loyalty and hence, substantial business value. 

Reimagining customer journeys with an AI lens
Contrastingly, in the age of AI, enterprises can completely reimagine customer journeys and become more productive in software engineering and operations. Forrester predicts the global average customer experience will improve for the first time in three years with Generative AI augmenting personalization capabilities. Here too, those successfully deriving value from these technologies will correctly link the operational drivers of the experience to customer perceptions. They prioritize the customer’s stated and unstated needs and preferences while designing products, services, and experiences.

Laying the foundation for an AI-first, digital-ready enterprise 
AI-first, digital-ready enterprises will shape the future. To thrive, they must operate with start-up agility; rapid innovation, and automation, offering numerous competitive platform advantages. Customer-centricity remains crucial. 
This will mean embracing product-centricity to establish an operating construct that aligns the organization – its business capabilities, people, ways of working, and technology ecosystem – to the flow of value. Moreover, it will help align businesses with the present-day market demands and uncertainties. 

Product-centric approach enables organizations to re-imagine their business capabilities as products based on customer journeys and associated value streams. Product thinking improves inter-functional collaboration to sharpen focus on customer journeys. Here, capabilities and services are delivered like products by autonomous, cross-functional teams to orchestrate end-to-end customer journeys. Goal setting is through a framework for OKRs and layered across the teams involved.

This will augment the platform ecosystem, crucial to AI-first enterprises for accelerating product launches and innovation. For instance, a leading Indian life insurance company set up its unified sales app using the platform approach for leads tracking, sales, policy conversion and ongoing policy servicing. Sales agents use AI for recommendations based on historical and transactional data. This has streamlined sales and product launches whilst improving the customer experience.

Human-centric experience design is vital. Hyper personalization unlocks new marketing and sales avenues. For instance, a platform was designed to reimagine the remote viewing experience of a global tennis event followed by fans, players, coaches, and media. Customized for each type of viewer using intelligent tools based on AI, research and design, it is a benchmark in digital viewing, reporting, broadcast editing, and player training experiences. 

The key is to become data-driven. A super app using AI and analytics can tailor user engagements offering dynamic widgets and short-cuts from other apps. Users can self-tailor and engage with the entire super app ecosystem in resonance with their preferences. 
Designers must also team up with data and AI specialists and ethicists to ensure security, privacy, ethical and green practices, and compliance needs are properly incorporated. 

For future readiness, enterprises must rely on AI to anticipate trends, plan next steps, and innovate amid a constantly shifting landscape. Being data-first – armed with accurate and relevant data and connected data ecosystems – will help them harness the power of AI fully. 
Adoption of Agile methodologies with DevSecOps, SRE practices, and tooling are pivotal to achieving speed to value and facilitating layered innovation. Building on this, enterprises must invest in high-performance engineering with AI-led automation to create seamless customer experiences.

Aligning talent to the logical flow of value enables better inter-functional working. Gaps must be filled by acquiring skilled people from the creator (e.g. data scientists, econometrists) and consumer (e.g. prompt engineers) communities. 

Nabarun Roy

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Nabarun Roy is Executive Vice President, Group Head – Quality, Productivity & Delivery Risk Management at Infosys