Editorial
Nearly everyone in the tech industry agrees that artificial intelligence will have a significant impact on their organizations. But yet, 50% of marketing leaders believe inadequate AI adoption is holding their marketing organization back from achieving its goals. With the potential for these technologies to streamline efficiencies, fuel innovation and make room for more strategic thinking, the time to successfully implement AI and machine learning within your brand and marketing teams is now. Here are three factors you should consider: how to manage your data, govern emerging technology and encourage upskilling.
Build a Data Strategy as the Foundation
First, you need a strong data and information management strategy before you can properly implement any AI and machine learning technology. That means your data should be properly aggregated, classified, intact and have the right information lifecycle applied to it. Without that, you are building on top of a shaky foundation of information that will not yield transformative results. With more data being produced than ever before, having it in order is now especially critical.
Furthermore, one survey found that 60% of marketing leaders believe AI will have a significant impact on lead identification and 55% believe it will impact marketing optimization like A/B testing and SEO strategies. But without an understanding of where your proprietary data lives and how to use it effectively, it’s difficult to start yielding meaningful business results. AI can help automatically classify data (like documents, inbound leads, excel files, etc.) that is otherwise cumbersome to do so manually. Classification including geography, priority level, type of inquiry can even be embedded into a document as metadata — that way, marketing teams can more easily extract value from lead lists, find the right excel files or even pull together key performance indicators quicker based on tagging campaign results.
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Govern Safe and Smart Usage
Second, to scale effectively, you need to make it easy for your teams to do the right thing. I’ve argued this before when discussing data governance, using the analogy that automating certain rules is like putting the bumpers up at a bowling alley to set yourself up for success. When it comes to AI, tools like ChatGPT, for example, should not be used with proprietary information because your employees run the risk of sharing material nonpublic information (MNPI) externally. But without a viable alternative or the right education, your teams may still use these tools to reap the productivity benefits.
That does not mean that you should ban AI usage outright, like some large companies are today. In fact, 56% of marketing leaders see greater reward than risk in generative AI. To mitigate the risk, you can deploy solutions like Bing Chat Enterprise, which keeps all corporate information confidential while still fueling efficiency and shifting focus to more strategic tasks.
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Encourage Continuous Learning and Adoption
Third, facilitate a growth mindset around AI adoption within your team. Encourage people to try new ways of working, and provide learning and development opportunities as needed. For example, some organizations may consider offering a monthly AI update with tips and tricks on how their organization is safely and creatively using this technology. Within the marketing department, this could mean how to use generative AI for identifying keywords for SEO, or how to develop new content for email campaigns, thought leadership and podcasts. You may also provide funding for individuals looking to expand their knowledge with more formal education and online courses, so they continue to grow and stay engaged.
Employees should not view AI as a threat, as only 4% of executives plan to reassess roles and reduce headcount as a result of AI. It’s actually an asset to their career growth and something that can make them a stronger contributor. In fact, LinkedIn predicts that the skills required for many jobs will change by 65% by 2030 due to the rapid development of new technologies.
Ultimately, laying the foundation for successful AI and machine learning within your team requires alignment in three key areas: your data strategy, how you roll out and govern technology usage, and what type of culture you facilitate to fuel innovation. With organizations that invest in AI seeing a revenue uplift of three to 15 percent, it’s critical to start now, and beginning with your marketing and brand organization can seed the change you want to see.
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