MarTech

2024/08/26

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Cutting through the Generative AI Hype in B2B

The landscape of business is undergoing a seismic shift, driven by the rapid advancement of generative AI. While the potential of this technology is immense, it's often shrouded in hype and misinformation. This report aims to cut through the noise, providing a clear-eyed analysis of generative AI's real-world applications and implications for B2B businesses.

A United Front of Doubt and Confusion

Boston Consulting Group shares some eye-opening stats: 62% of companies are struggling with a talent and skills gap, 47% are unsure where to invest, and 42% are still figuring out how to deploy AI. Only a daring 5% claim they’ve successfully scaled and are thriving with generative AI.

Gartner adds that while over 90% of enterprise organizations are pondering their AI strategy, only 11% have deployed an AI solution. Even among professionals who see AI's potential to boost sales, 45% still feel overwhelmed by the constant barrage of AI tools and applications.

Rain Group highlights a major training gap: 85% of sales professionals haven't received formal training on using AI in their roles.

United in hesitancy and confusion with AI

The hype would have us believe AI is a magic bullet for success, ready to deliver ROI at the snap of a finger. But the reality check is harsh: it's far from easy, and much of the advice out there is ungrounded. The so-called AI experts of today were the crypto and EFT gurus of yesterday.

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Today’s Tools Just don’t cut it

Using GPTs today feels like wrestling with a DOS prompt from the 1980s that somehow ended up in our modern world and decided to throw a party. It shouldn't be this complicated.

Embedded AI solutions are so generic that they might as well be reminding baby boomers to go grocery shopping. These AI systems have a bland, one-size-fits-all view of the world. Sure, they can tell you about farming techniques in the Sub-Saharan Desert, but they struggle to understand what makes your solutions better, different, or more valuable than your competitors'.

What’s the next step?

1. Develop a plan

You don't need to set everything in stone, but you can't go without a clear direction. With AI evolving, it's better to focus on flexibility over rigidity and on an adaptable framework rather than strict guidelines.

Make a plan to get a clear direction

Think of your strategy as a sketch, not a detailed blueprint—specific enough to provide direction but flexible enough to adapt. Start with clear business goals and identify the initial solutions to achieve them. This is where I highlight “use cases.” At this stage, bring your current thought leaders together, but avoid getting bogged down in politics.

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2. Start small, but think strategically.

AI technologies are evolving, so stay agile, adaptable, and curious. This mindset allows you to pilot AI solutions that tackle specific challenges without needing to revamp your entire system.

Focus on areas where you can achieve quick wins, whether it’s improving customer service, streamlining operations, or personalizing marketing efforts. Treat these initial projects as learning opportunities, using the insights and data gathered to shape broader strategies.

Foster a culture of experimentation where successes are scaled and failures become valuable lessons. Stay forward-thinking yet grounded, ready to adapt as new advancements arise.

3. Context matters most

Move your focus from prompt engineering to training data. Right now, you might be limited to 4,096 characters in a prompt, and even if that limit were increased, it wouldn’t solve the problem that generative AI knows nothing about what makes your business unique. You need to train it.

GenAI doesn’t grasp your market positioning or value propositions—it requires your guidance to become a valuable asset. Use the use cases identified earlier to feed it rich, context-specific data that educates it on what sets your business apart.

Whether you call it strategic nurturing or training data, this step transforms generative AI from a generic tool into a partner, helping you become more effective and more efficient.

Considering the context of using AI

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4. Productivity vs. Performance: What's Your Focus?

This is a crucial factor in AI adoption. Prioritizing performance (efficacy) is the first step—ensuring that AI solutions achieve your desired outcomes. Without demonstrating AI’s ability to improve decision-making, customer engagement, or other key metrics, focusing on productivity (efficiency) is like speeding up when you're lost.

Start by confirming that AI-driven strategies can tackle your business challenges and goals. Once you’ve established that the AI performs, using it to streamline processes will enhance these successes, making efficiency gains not only quicker but also smarter and more impactful.

5. Balancing People, Process, and Technology

AI is here to stay, and it’s time to move past resistance and understand how this technology will impact people and processes. Seek out tools that provide valuable context, are user-friendly, and deliver clear benefits to your team.

Be prepared to train and onboard your team with these tools. It might be like learning to ride a bike—expect some falls, but they hurt less when you're starting out. Embrace the process, get back up after each setback, and approach it with the same enthusiasm you had as a kid!

Generative AI is a transformative force, but its true potential in B2B lies in practical application, not hype. By understanding its strengths, limitations, and ethical considerations, businesses can make informed decisions about its integration. While challenges remain, the opportunities for increased efficiency, innovation, and customer satisfaction are substantial. As the technology matures, its role in B2B operations will grow more significant. The key to success is a balanced approach that leverages AI's capabilities while reducing risks.

This blog has aimed to provide a clear, actionable roadmap for businesses navigating the complex landscape of generative AI. By cutting through the hype, we hope to empower organizations to make data-driven decisions and unlock the true value of this groundbreaking technology.

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