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Perils and Promise of Gen AI for B2B Tech Marketers

4 Perils of Gen AI in B2B Tech Marketing

“Technology is a double-edged sword. Fire kept us warm and cooked our food but also burnt down our houses. Every technology has had its promise and peril.”

Ray Kurzweil at the 2015 Exponential Finance Conference

Inventor, futurist, and bestselling author Ray Kurzweil’s words could not be timelier amidst the meteoric rise of generative artificial intelligence (gen AI) platforms. Chatbots, text generators, and visual generation tools give marketers the promise of saving time, reducing repetitive tasks, and boosting productivity.

Yet for all its promise, generative AI also brings potential perils. This is especially true for B2B tech marketers, who must navigate a landscape where accuracy, differentiation, and compliance are crucial for accelerating their go-to-market efforts.

Why the perils of gen AI should matter to B2B tech marketers

Generative AI has become one of the most rapidly adopted technologies in history. ChatGPT hit 100 million users within just two months of its launch, making it the fastest-growing consumer application ever.

This adoption is particularly evident among marketers, who have embraced AI more than any other professional group. A recent HubSpot survey found that 64% of marketing professionals use gen AI tools in their daily jobs.

Due to the extremely fast adoption of gen AI, many organizations aren’t fully prepared for the widespread use among their employees and the potential risks that come with it. In a report from McKinsey, only 21% of respondents said their organization has risk policies in place for gen AI. This leaves much of the onus on employees to determine whether AI tools and its outputs work for them.

Whether you’re already using AI or just considering it, it’s critical to understand the potential pitfalls. To help you in this process, we’ll discuss four of the greatest perils we predict for B2B tech marketers leveraging AI tools – and how you can mitigate them to accelerate sales, revenue, and adoption.

The 4 perils of generative AI in B2B tech marketing

Peril #1: Inaccurate Information

In a survey of over 1300 businesses, HubSpot found that the greatest challenge facing B2B tech marketers is inaccurate information. Gen AI tools can produce factually incorrect, outdated, or completely misleading content. Just check out the fake law cases that ChatGPT created.

Source: HubSpot

This is particularly problematic in B2B tech where audiences are technically savvy and demand accurate information. Relying solely on text generators may result in factually incorrect data sheets, FAQs, and product guides, which could alienate your audience and cause them to lose trust in your brand.

Mitigation strategy: Ensure that any AI-generated content, especially content that contains specific product details and technical information, is rigorously confirmed by a subject matter expert.

Peril #2: Homogenization

The B2B tech world is extremely competitive. To stand out from the crowd, you need to create authentic, impactful engagements at every touchpoint along your buyer’s journey.

While gen AI can produce content quickly, these tools often spit out material strikingly similar to existing content. This can pose a challenge for B2B organizations looking to differentiate themselves. If your competitors use gen AI in the same tech space, you risk all sounding the same.

Mitigation strategy: Rather than relying on gen AI for entire tasks, consider using these tools for outlines, ideas, or for the final polish. Be sure to maintain an authentic, human touch in all your customer-facing outputs.

Peril #3: Ineffective personalization

While gen AI has the potential to enhance personalization (HubSpot even points to it as one of its main promises), getting personalization right can be challenging without the appropriate resources.  

AI-driven personalization requires vast amounts of high-quality data to be effective, but many businesses struggle with data availability and quality. If the data fed into AI systems is inaccurate or incomplete, the recommendations and personalization generated can miss the mark, leading to irrelevant or even off-putting customer interactions​.

Mitigation strategy: If you plan to use gen AI for personalization efforts, invest in high-quality data collection and management practices, including advanced customer data protection.

Peril #4: Ethical and legal considerations

Navigating the ethical and legal landscape of AI usage is one of the most significant challenges for B2B tech marketers.

In a recent report from McKinsey, cybersecurity, intellectual-property infringement and regulatory compliance top the list for risks associated with gen AI adoption.  

Source: McKinsey & Company

While the goal isn’t to scare you away from using AI entirely, it’s important to consider data usage thoughtfully and responsibly.  

Mitigation Strategy: Where possible, anonymize customer data before feeding it into AI models to protect individual identities while still gaining valuable insights.

Focus on authentic, impactful customer touchpoints

While gen AI, like any technology, has its promise, it’s important to be aware of its possible perils in the world of B2B tech marketing.

With potential risks like inaccuracy, homogenization, ineffective personalization, and noncompliance, gen AI should be viewed as a single tool among many for marketers, not the entire toolkit. It should complement rather than replace your human touch.

Your focus as a B2B tech marketer should always be to create authentic, impactful engagements with your audience. By prudently and appropriately harnessing the power of gen AI tools for this core goal, you can stand out, resonate, and break through to your audience.

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