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AI maturity framework for enterprise applications

By Tanvi Kakodkar posted Wed November 04, 2020 09:36 AM

  
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Introduction

Artificial Intelligence (AI) is transforming how we live, work and do business. From smartphones to smart factories, AI is ubiquitous – and whether we realize it or not – it is influencing our everyday interactions with businesses. AI has disrupted our lives by entering the entire gamut of areas like recommendations during ecommerce purchases, personalized video streaming options, predictive texts while typing, and prioritizing social media feeds.

As organizations move on their AI journey, they have to infuse AI in their enterprise applications and sometimes build new AI offerings from scratch. The use cases for AI infusion span industries and product categories, and cover a wide spectrum ranging from providing insights, recommending the next best actions, predicting and forecasting business outcomes to fully automating business processes. Most organizations start their AI journey and soon want to scale AI but get stuck during the process. Identification of all AI capabilities, technologies, client adoption levels, and value derived from AI are some salient metrics that govern the journey’s success.

At IBM AI Applications, we are infusing AI into enterprise products ranging from asset management, facilities management, supply chain management, engineering lifecycle management to weather business solutions. Our experience of infusing AI and delivering value to clients has been collated in this white paper and has led us to create the AI Maturity Framework. This framework, now a standardized methodology in our organization, is a measure of how mature AI is in any enterprise application. We deliberate on the factors that contribute to AI’s maturity and how this is a journey and not an end state. This framework prescribes a methodology for assessing business and technical aspects of AI.

This white paper is a ready reckoner for enterprises across industries to measure the readiness and completeness of AI applications that they have implemented. These enterprises are the ones who have either infused their existing legacy applications with AI or have bought new bespoke AI applications or even those who are evaluating independent software vendors (ISV) selling specific AI applications. In the same light, this whitepaper would be used as a tool by ISVs and system integrators (SI) to measure the maturity of the AI applications that they build and implement for clients. The factors contributing to the maturity are both business- and technology-centric, hence the measurement will be a combination of both. The value of the maturity framework can be derived by a spectrum of business-oriented roles like CXOs, product managers and business leaders who are correlating the extent of the impact of AI to their revenues. The maturity framework is also relevant for technical roles like enterprise architects, application developers and data scientists who can measure the extent of advance AI features that they have included to advance the solution.

Download Whitepaper


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