How to Pilot Generative AI in your Enterprise

Organizations are planning or in the process of running PoCs for generative AI. According to the MIT Technology Review, 76% of business leaders say their companies are ready to adopt generative AI in their workflows.??

According to Gartner, 45% of organisations have seen an increase in AI investment since ChatGPT was released, and 68% of executives believe that generative AI benefits outweigh its risks.??

Generative AI opened up new areas and enabled broader opportunities with multimodal and multilingual AI for different Data types and artefacts, including text, code, images, video, music, speech and designs (e.g., 3D, parts and buildings).??

AI will improve human collaboration and relationships by transforming the lives of people with special needs.

Humanoid robots will be new companions, and AI Agents will be new teammates, which enhance human intelligence. ??

Data is a New MOAT, and Sovereign AI is evolving for the use cases.??

A generative AI Pilot might cover different use cases, for example. ??

• Intelligent Document Processing - Automate loan application review, extract key facts from financial statements, and generate reports – all with extraordinary accuracy.??

• Personalized Economic Forecasting - Using AI to analyze vast datasets and predict future cash flow needs, enabling businesses to make data-driven decisions.??

• Using Automated Code Reviews and Test Cases application to improve developer productivity and experience ??

• Leveraging image generation and content creation to create marketing materials and Product knowledge base ??

• Synthetic Data Generation - Address data gaps Challenges and train Ml models to improve speed to market with new AI solutions??

• Customer Support and Experience – Handling multiple customer inquiries simultaneously, responding instantly to frequent questions and troubleshooting issues.??

Companies do not need to opt for large language models. Leaders have to look into the context of the domain, who will use your AI, and where you will use the AI.

In Some Cases, they must consider?Response time, cost, data privacy, and specialized needs like On-Device Intelligence to finalize the business case.??

SLMs (small language models), LAMs (Language Action Models), DLMs (Domain Language Models), and traditional?ML and Deep Learning Models?have many applications, particularly for organizations with specialized needs.

On Device Intelligence, Apple, hugging Face and Microsoft launched small Models for Specific use cases and needs.??

Different implementation strategies exist for the use cases, from customization of models, building from scratch or buying from an external Cloud provider or API provider. ??

We are shifting from models to compound systems, and Organizations must adopt Data-centric AI and build Compound AI Systems with Agentic workflow.?

RAG is an example of compound systems ?

Large enterprises are looking to adapt to generative AI to improve efficiency and productivity, enhance creativity and innovation, Improve decision-making and analytics, and personalize customer experiences. ?

Enterprises also enhance their services to create a competitive edge and address risk management and regulatory compliance. ?

Steps to take for Pilot Generative AI ??

1. Identified The Business Use Case ??

???????? ???????Get input from the business on potential use cases.??

??????? ?????????Align use cases to your business and IT strategy.??

??????? ????? Select the best use cases from among the many available options.??

2. Prioritize the Business Use Case ??

3. Understand data requirements.??

4. Assemble the small team ??

5. Design Considerations and Plan the Pilot ??

????????????Determine Pilot Objectives and?KPIs??

??????????????Determine Risks and Mitigations for Pilot Use Cases??

??????????????Decide on the Deployment?Approach?

6. Deploy, monitor, and evaluate the pilot?

7. Iteration on the Outcomes and align Business Value ??

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