4 Questions to Ask Before You Invest in Artificial Intelligence: AI for B2B Marketing Leaders

On October 15th, 2024, Amazon Web Services (AWS) showcased how it supports companies to shift generative AI-driven technology from experimentation to production: so what’s next in AI for B2B marketing leaders? In just a few short years, artificial intelligence has transformed at great speed and scale from a niche research area into a cornerstone of modern business, revolutionising industries from healthcare to finance—and marketing is no exception. In a Q&A, Rahul Pathak, AWS’ vice president of generative AI and AI/ML go-to-market, addressed his customers’ AI challenges. He outlined how customers want to achieve a business outcome and get it right. He explained that they need to define what they are trying to accomplish and then work back from there while asking how AI can help. But with thousands of AI marketing solutions flooding the market, where do you start? 

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When integrating AI into any process, it’s better to start with initiatives that offer the highest impact with the least effort and risk. These “low-hanging fruit” opportunities can provide quick wins and build momentum for more extensive AI adoption. Here are four questions you can ask before investing in AI to help determine if you are investing in the right solution.

1. Easy implementation

Complex solutions may promise big returns, but if you are starting your AI journey, the complexity may cause them to stall. AI solutions that are easy to implement and adopt typically have the following characteristics:

• Plug-and-play or SaaS solutions that don’t require coding or IT infrastructure changes (a SaaS solution will sidestep negotiations with your IT department).
• User-friendly interfaces that marketing teams can navigate without extensive technical training.
• Compatibility with existing marketing tools and platforms.

2. Quick wins

Look for solutions with defined business outcomes that do not require extended build, integration, or training periods. Projects that can deliver quick results demonstrate the value of bringing AI into your marketing department. Look for solutions that can:

• Be deployed and show measurable results within 1-3 months.
• Address immediate pain points or inefficiencies in current marketing processes.
• Can improve key performance indicators (KPIs) such as conversion rates, customer engagement, or lead quality.

3. High ROI potential

To justify the investment in AI, you should focus on applications that offer significant returns:

• AI solutions that can automate time-consuming tasks, freeing up marketers for
• more strategic work.
• Applications that can reduce costs or measurably increase revenue.
• Solutions that scale easily, providing increasing returns as they are adopted.

4. Minimal disruption to existing processes

To ensure smooth adoption, prioritise AI solutions that:

• Integrate seamlessly with current marketing workflows.
• Require minimal changes to team structures or job roles.
• Can be implemented without extensive retraining.

By focusing on initiatives that meet these criteria, you can quickly demonstrate the value of AI, build internal support for further adoption, and gain a competitive edge in your marketing efforts. However, as Rahul Pathak explained at the beginning of this chapter, you need to define what you are trying to accomplish and then work back from there while asking how AI can help. If that seems too wide a proposition, download your free copy of AI for B2B Marketing Leaders where I talk about experimenting with AI in safe environments.