5 Steps for Businesses to Capitalize on Generative AI

Generative AI is already a transformative force in today’s business landscape, and it’s only getting started.

As the team at Compoze Labs continues to engage in conferences, thought leader gatherings, and university events, the conversation around Generative AI has become increasingly focused on where to start and how to invest. After the AI hype and rapid innovation of 2023, we anticipate a lot more real Gen AI solutions going to production and making large impacts on how our clients operate next year. Here, we’ll explore key approaches for businesses looking to unleash the power of Generative AI during 2024 and beyond. 

Step 1: Don’t Let Fear Hold You Back

Executives are feeling the urgency to understand how Generative AI can impact their businesses, especially during end of year budgeting cycles. And rightfully so – Experience with Generative AI is becoming a competitive advantage, separating forward-thinking companies from their peers. Generative AI is creating both new business growth opportunities and areas for cost efficiencies.

But fear, uncertainty, doubt and fear of missing out is actually delaying many organizations and individuals from jumping in.

At Compoze Labs, we advocate for diving in sooner as the learning curve with Generative AI is long. And know if you don’t, your competitors are.

Step 2: Dive in Starting With a Strategy and Stay Focused

Start the Generative AI journey with a AI strategic assessment to align business and technical goals. Any targeted initiatives should be complemented by rapid proof of value or prototypes, providing tangible experiences on the “art of the possible,” while building internal support around Gen AI concepts. 

Strategic assessments should pinpoint real pain points, enabling businesses to construct end-to-end real examples that showcase Generative AI's technical strengths but also current limitations. 

Dive in with impactful use cases, such as automating tasks across Sales and Marketing functions, or implementing Retrieval Augmented Generation (RAG) based chatbots for Customer Success or Operations. Demonstrating efficiency gains in specific functional areas helps build a compelling business case for broader Generative AI adoption and creating the necessary expertise around building, running, and improving Gen AI services.

Step 3: Anticipate and Plan for Rapid Change in AI

The rapid evolution of Generative AI tools demands a flexible approach. While many developers may be averse to rework, planning for change is essential.

Choose frameworks that allow easy adaptation to new models and technologies. Embrace hybrid approaches when necessary, considering model strengths, costs, and speed to market. Tools like LangChain and LLM orchestration facilitate adaptability, isolating business logic from specific models or frameworks. 

Embrace rapid change and innovation as a part of the learning process, and quickly adopt updated models and frameworks for a faster path to value.‍

Step 4: Customer Feedback is Crucial - Use It to Your Advantage

Evaluating, testing, and tuning large language models (LLMs) is necessary and will require a different approach than traditional software testing. Acknowledge the variability in model responses and the ongoing continuous improvement cycle required.

Customer feedback is also a crucial component for refining Generative AI offerings and adoption. Collecting customer data is key in building a data flywheel to improve AI service results and evolve. As a relevant example, OpenAI's release of ChatGPT 3.5 centered around gathering more real user input (vs. model APIs) to enhance model performance and address user behaviors more quickly. Launch, collect, learn and adapt.

Step 5: Bet on the Future

Regardless of market dynamics, the growing business impact and novel applications of Generative AI are undeniable. 

Generative AI solutions often start as simple prototypes and rapidly evolve with focused tuning and the integration of knowledge bases. Numerous foundational model launches in Nov 2022 and 2023 redefined what was viewed as possible from Generative AI. OpenAI ChatGPT, Google Gemini, Anthropic Claude, Mistral MoE model, Meta Llama and other foundation model builders are not slowing down. The key is to bet and plan on continued model and framework progress vs. playing catch. 

Businesses that embrace and learn from these advancements early on will be at the forefront of AI-driven waves in technology and business. 

The Bottom Line

Generative AI is not just a technology; it's a strategic opportunity for businesses to innovate and stay ahead in an increasingly competitive and shifting landscapes. As businesses navigate the uncharted territories of AI, the journey promises exciting improvements and capabilities that will shape the future of numerous industries. 

Embracing Generative AI sooner will position your business to lead in the era of intelligent automation and all the opportunities that come with it.