Business leaders across industries can unlock transformative possibilities with AI. In today’s digital marketing landscape, AI is an essential member of marketing teams, creating hyper-personalized language, unlocking enterprise creativity, and helping teams engage with more consumers than ever before. AI picks up where people leave off, allowing human marketers to do what they do best – innovate and strategize.
In spite of AI’s clear benefits, there’s still a gap between trust and adoption. The Marketing AI Institute’s 2021 State of Marketing AI Report revealed that 52% of marketers say AI is very or critically important to the success of their marketing in the next year. Yet, only 17% had plans for wide-scale AI adoption.
It’s getting late in the game to be an early adopter of AI. According to IBM, a whopping 82% of CEOs at companies that outperformed their peers championed AI technologies as successful markers of digital transformation. If marketing leaders want to stay competitive, AI isn’t just a “nice to have” – it’s a “need to have.”
That’s all easier said than done. Scaling marketing AI to the enterprise level presents its own set of unique financial, strategic, and cultural challenges. But those obstacles are no reason to balk at AI altogether. Here are some tried and true strategies that help make scaling AI to the enterprise level the marketing superpower it should be.
1. Take a Strategic Approach
If marketing AI is the new Superman, then coming in without a strategy is its kryptonite. No matter how cutting-edge your AI tech might be, it won’t be very helpful if you don’t have a clear plan that enables AI to reach your goals.
AI cannot (and should not) replace your entire martech stack. What it can do is perform narrow, hyper-specific tasks at superhuman levels. Marketing leaders must first map out their strategic vision – one that incorporates an understanding of their existing martech stack and where AI might fit in – in order to unlock the ultimate potential of scaling marketing AI. Before diving headfirst into leveraging AI in their marketing strategies, business leaders should:
- Audit current marketing processes to scope out where the benefits of AI are most helpful.
- Identify real use cases where the power of AI can have the most impact.
- Map out clear and time-bound marketing experiments to test where AI works and where it doesn’t.
- Establish KPIs to measure each new experiments’ success.
2. Educate and Engage Leadership
It’s hard to get the hang of a new tool at first. There’s a chance that one or more of your pilot AI projects will fall short of your goals. These temporary setbacks cannot stop your teams from adopting AI. Keep leadership advised of the possible challenges and early complications that may come from scaling AI in your martech stack.
When AI implementations don’t go as planned, take it as an opportunity to learn. Reflecting on what worked and what didn’t to create another game plan can turn a prior misstep into a huge victory. The key is to consistently engage with leadership teams along the way so expectations can be informed, realistic, and ultimately productive.
Having major players in your organization on your side could make or break your AI goals and keep marketing leaders and CMOs from getting sidelined by company leadership. Securing C-level support is a matter of:
- Sharing clear plans: It’s easier to back a project when you know what its goals are.
- Connecting AI programs to important business goals: Business leaders are more earnestly invested when they understand the why behind AI.
- Communicating — and communicating again: Consistent engagement ensures no surprises and helps set clear expectations.
3. Practice Informed Buying Decisions
We’re well entrenched in a new digital age, and that means there are a lot of different AI solutions on the market to choose from. Marketing professionals who are able to connect their real business challenges directly with specific AI-powered technologies are the ones who will ultimately come out on top.
Remember: AI is an investment. Like with any investment, you’ll want to be sure you’re making an informed decision. AI vendors might claim to use high-end technologies, but it doesn’t necessarily mean that their solution is the right fit for your business needs. To ensure that you’re buying the right tool for the right problem, considering asking vendors these questions:
- What are the primary use cases for this AI-powered solution?
- How is AI specifically used in this product?
- Does this solution integrate with other technologies in our organization’s current martech stack?
4. Prioritize Use Cases to Pilot
AI is built for specific, hyper-specialized tasks. It’s designed to pick up the slack where humans can’t — tackling rote, repetitive tasks like optimizing email send time or writing ad copy at scale. Audit your current marketing strategies for team responsibilities that could be more intelligently performed by AI, and then plan out specific use cases from there.
When implementing AI, it’s important to remember to start small. Pursuing company-wide AI transformation right out of the gate could be costly, risky, and take an extremely long time to reap benefits. A novice runner doesn’t run a marathon in the first week – why would business leaders do the same with AI?
Start out with smaller AI pilot projects because they’re feasible, meaningful, and easily measurable. For instance, automating send time for one set of email nurtures implements specific and measurable change, making it easier to test for success. These small wins can build up over time, helping your AI projects gain momentum by letting your organization grow comfortable with AI tech and progressively realize its value.
5. Train Your Team and Explore AI Together
As our world grows more digital, AI will gradually integrate into every aspect of marketing. Leveraging AI technology is key for businesses hoping to stay competitive in an ecosystem with more touchpoints for customer engagement than ever. Yet, Marketing AI Institute’s 2021 State of Marketing AI Report reveals that 82% of marketers don’t have internal AI-focused education and training. Meanwhile, 70% of marketers say lack of education and training is the number one barrier to widespread AI adoption. AI education must be a company-wide priority. As new technologies evolve at an exponential rate, these initiatives should be comprehensive and constantly expanding.
Consider offering training in the following areas to keep your teams ahead of the curve:
- Data analytics
- Pilot AI program development
- AI and smart content planning
Adopting AI at the enterprise level is no easy task, but it is achievable. Establishing clear strategies, launching small-scale pilot programs, and identifying where AI fits best in your current marketing strategy are key ways to mitigate marketing AI growing pains and unlock the best results for your organization.
Companies must approach AI in marketing with a sense of urgency. Marketers who act now will create a significant competitive advantage for their organization that could define the next generation of digital marketing. Those who adopt and those who don’t could be looking at significantly different careers in the near future.
Learn more about the promise of AI for marketing and how you can adopt it using a 10-step playbook in AI for CMOs: The Real-World Playbook for Digital Transformation – a collaboration between MAII and Persado.
Share
