By Prakash Balasubramanian
Generative AI adoption is the buzzword for businesses currently. While from a technology perspective, it is redefining the way we operate, enterprises are slowly navigating through the challenges and complexities in its adoption.
Gen AI adoption requires a clear roadmap for near term benefits and long-term transformation. All decision makers, technology leaders and change managers, must focus on understanding four key areas:
Evaluating the use case of Gen AI
Gen AI today is best suited in the areas of Content Generation and Conversational AI. These can be applied to areas of business to bring down operating costs and drive process efficiencies. Areas like customer care and marketing content management, are a couple of use cases where businesses can see immediate benefits. Software engineering is another area where Gen AI would drive significant productivity gains.
Companies need to define what kind of productivity boost you are seeking. Is it mere automation to reduce manual, and repetitive tasks? Or does your team need to reduce errors in data management? Data optimization is a broad spectrum. Would you benefit from predictive analytics or personalized data? Work with experts in the field to define it.
BFSI businesses have benefited from predictive analytics in mitigating investment risks. The retail and telecom industry has benefited from chatbots with personalized query management with issue resolution suggestions.
Assessing the resources at hand in deploying Gen AI for use cases
Only 1% of the global workforce has the skills needed to develop and deploy AI (McKinsey, 2023). Enterprises need two types of Gen AI workforce, ones that would be consumers of Gen AI and the others who create. Consumers use Gen AI tools to improve their day-to-day tasks. The creators work on developing algorithms and models to suit business needs. Companies can rapidly roll out training programs for the consumer side of skills. For the creator side, check your existing pool of talent for a wide range of skillsets including AI and ML specialists with expertise in algorithms, models, and AI techniques. Assess training and upskilling requirements for potential workforce. Work with gen AI skill-training enterprises who can offer training across all stages of adoption including ideation, design, test, implementation, innovation, and monitoring.
Evaluating the technical and business impact of leveraging Gen AI
Check its ability to generate content or solution for technical impact (improved accuracy, relevance, and consistency), business impact: (improved CX, operational efficiency, and cost savings). As enterprises leverage Gen AI, it’s critical to evaluate business and technological benefits. From a business standpoint, Gen AI can impact topline through solutions focused on customer experience, reduce bottom-line through solutions focused on process efficiencies like automation in marketing content generation. Gen AI can also help transform your IT organization through highly efficient software engineering processes. Businesses need to evaluate critical elements like ethics and security as they make their Gen AI investments.
Ensuring the readiness of data through its planned collection, curation, and governance
Not all data are useable, not all data are readable (AI/ML-model-wise). All gen AI solutions are powered by a data foundation. It is primary to train and improve the ML models. Now, how do you “prepare data,” that can be used? Simple – focus on identifying the data requirements for specific use cases – the kind of data sources to be assessed: text, image, or audio? Then curate it. This includes data mapping, fixing anomalies, and ensuring that quality data is fed in the system. Once you’ve curated it, label and deploy it. And always ensure manual and automated quality check to assess live performance.
Privacy, security, and confidentiality – three prime areas in gen AI data management
Develop a gen AI risk assessment framework within the organization that offers clear view in:
- Preventing data leaks
- Ensuring data reliability
- Define ownership
- Assess and fix biased data output or unethical responses
Plan change management with a governance team and always track periodic impact. Identify areas of improvement and be agile in implementing it.
Gen AI is an evolving technology currently. Successful early adoption can offer several benefits – proper planning and a clear roadmap will help generate desired outcomes.
(The author is Prakash Balasubramanian, Executive Vice President, Engineering Solutions, Ascendion, and the views expressed in this article are his own)
