Overcoming AI Inertia: 6 Considerations to Start Your Gen AI Journey

The buzz around AI, particularly generative AI, is undeniable. It’s the talk of the town, yet many businesses remain on the sidelines, intimidated by the perceived complexities of building a solid business case. My advice? Don’t overthink it (to an extent). Sometimes, back-of-the-napkin calculations are all you need to get started.

Recently, I had the pleasure of joining a panel discussion with colleagues from Lucidworks, Google Cloud, Chamfr, and Test Equity Group to explore the topic of “Moving AI From Hype to Reality: Implementing AI in B2B Commerce.” You can catch the full on-demand webinar below, or continue reading for some key takeaways.

The Missing Piece: A Comprehensive Gen AI Strategy

While starting small is essential, our 2024 Gen AI Benchmark Survey reveals that businesses need more than just enthusiasm to succeed. A staggering 42% of companies are struggling to see results from their Gen AI initiatives, and only 25% have reached full deployment.

The message is clear: LLMs (Large Language Models) alone are not enough. A comprehensive Gen AI strategy that addresses cost, accuracy, and security is a key missing piece to move projects out of the pilot phase.

Other common hurdles to overcome are:

• Pushing Past Internal Resistance: Employees may be hesitant or resistant to adopt new AI technologies, fearing job displacement or a steep learning curve. Learn to clearly communicate the benefits of Gen AI and how it can empower employees to work more efficiently and creatively.
• Integrating AI with Existing Systems: Seamlessly integrating Gen AI into your existing technology stack and workflows can be complex and time-consuming. Choose AI solutions that offer robust APIs and integration capabilities. Work with experienced partners or consultants to ensure smooth integration and minimize disruption to your operations.
• Measuring ROI: Quantifying the return on investment (ROI) of Gen AI initiatives can be challenging, especially in the early stages. Establish clear key performance indicators (KPIs) aligned with your business objectives from the outset. Track metrics such as increased productivity, improved customer satisfaction, or reduced costs to demonstrate the tangible value of your Gen AI investments.

Key Learnings and Tips from the Trenches

Brian Land, VP of Global Solution Engineering at Lucidworks, shared valuable insights from his team’s hands-on experience deploying Gen AI projects.

1. Cost-Conscious Scaling: While LLM costs have decreased, mindful scaling is key. →  Explore cost-effective options like open-source LLMs or fine-tuned smaller models for specific tasks. Leverage vector databases to reduce the frequency of expensive LLM calls, and implement techniques like quantization and pruning to optimize model size and inference speed.
2. Security and Accuracy First: Establish robust security protocols from the outset to protect sensitive data and prevent unauthorized access, mitigating risks associated with insecure or inaccurate Gen AI. → Implement techniques like Retrieval Augmented Generation (RAG) to ground responses in verified information and reduce the risk of hallucinations. Using semantic vector search can also enhance accuracy and ensure data security, especially in B2B environments where precision is critical.
3. Foster Adoption Through Trust: Successful scaling hinges on user adoption. → Build trust by providing training and support, empowering your team to confidently leverage Gen AI tools. Provide comprehensive training programs and create clear guidelines for responsible AI usage. Encourage open communication and feedback channels to address any questions or hesitations.
4. Strategic Project Selection: Begin with high-impact, low-complexity projects to showcase Gen AI’s value and secure buy-in for further expansion. → Focus on use cases with quantifiable ROI, like automating repetitive tasks, improving customer service response times, or personalizing product recommendations.
5. Explore Diverse Use Cases: Don’t limit Gen AI’s potential. → Conduct workshops or brainstorming sessions to identify potential use cases across different departments. Consider opportunities to enhance both customer-facing experiences (e.g., product recommendations) and internal operations (e.g., document summarization) to drive efficiency across the board. 
6. Data as Your Foundation: High-quality, well-structured data is the cornerstone of successful Gen AI. → Implement data cleaning and normalization processes. Establish a data governance framework to ensure data accuracy, consistency, and security. Regularly evaluate and update your data strategy as your Gen AI initiatives evolve.

Moving Beyond the Pilot Phase

Don’t let your Gen AI initiatives stall in the pilot stage. To successfully transition from experimentation to enterprise-wide value, it’s essential to adopt a structured approach. Start by clearly defining a practical use case, ensuring it aligns with concrete business objectives. 

Recognize that Generative AI is not just about LLMs; a robust orchestration engine is vital to manage the entire lifecycle of your initiatives. Prioritize data acquisition, ensuring you have access to high-quality, relevant data, while implementing stringent security measures to protect sensitive information. Leverage techniques like Retrieval Augmented Generation (RAG) and semantic vector search to bolster the accuracy and reliability of your applications. 

Next, carefully select and implement the appropriate LLM model(s), and establish access controls to manage interactions. Maintain cost control by understanding the financial implications and exploring optimization strategies. Finally, continuously track the performance of your initiatives against your business objectives, using data-driven insights to refine your strategy and demonstrate ROI.

By following this structured approach, as visualized in Lucidworks‘ “Generative AI Path to Success,” you can ensure your Gen AI strategy is not only comprehensive but also aligned with your business goals, enabling you to move confidently from pilot to profit. Remember, successful Gen AI implementation demands a holistic strategy that encompasses the entire lifecycle of your initiatives, from use case definition to ongoing monitoring and optimization.

Image from Lucidworks, 2024 State of Generative AI in Global Business

Take the Next Step

• Watch the On-Demand Webinar: Gain deeper insights from industry experts on implementing AI and Gen AI in B2B commerce. Watch here.
• Explore Lucidworks’ Search Path Tool: Discover how AI and other capabilities can work together to deliver exceptional digital experiences. Build Your Required Capabilities Checklist with Lucidworks Interactive Search Path.

I’ll leave you with this: The time to embrace Gen AI is now. Don’t let fear or complexity hold you back. Start small, learn, and iterate to ultimately see some real traction from this powerful enabler of better digital experiences.