May 28, 2024
6 MINS

5 questions to ask before adding AI tools to your tech stack

From identifying specific use cases to determining ROI.
MarTech

Marketers: You can’t avoid integrating AI into your operations much longer.

But that doesn’t mean you jump off a cliff straight into the deep end, with a prayer rather than a plan. It’s only too easy to rush into AI implementation minus a clear strategy.

To ensure that you join the AI-powered future mindfully, rather than haphazardly, there are a few key questions to ask yourself as you add tools to your tech stack.

#1: What problem am I trying to solve?

That is to say: Why do you even need AI?

What gaps or inefficiencies have you identified within your current operations that are most credibly addressed with AI tools? Where are you filling a clear business need, rather than just chasing a trend?

According to OnlineGames CEO Marin Cristian-Ovidiu, impactful AI adoption is only possible after identifying specific scenarios where AI can improve or completely transform an existing process.

“If AI solutions exist that can significantly speed up processes, reduce errors, or unlock new capabilities in areas like user analytics or personalized content, then we consider these tools viable for addressing our specific needs,” he says.

Step one when considering tools to add to your own company’s own tech stack is to identify pertinent use cases that warrant AI.

It won’t work if you simply say “AI will help us work better and faster across the board.” Be granular.

Say your retail brand wishes to optimize digital advertising campaigns across multiple platforms for better conversion rates.

As you expand across more markets, you struggle with managing a growing volume of creative assets—and with keeping the ad strategy sleek and personalized.

You might then decide to integrate an AI tool like SmartAssets to help manage your brand’s extensive library of video and static image ads, or QuestDIY, which uses AI assistants to help draft surveys that can be deployed at scale.

Problem, meet solution.

#2: Is my brand ready to adopt AI tools?

Determining your organization or brand’s readiness to adopt AI starts with your long-term strategic goals.

“It’s important to bring key, cross-functional stakeholders, including your management, legal and IT departments together,” says Stagwell Marketing Cloud CEO Elspeth Rollert. “In other words, leadership needs to establish guardrails, and then empower teams to explore and experiment within them.”

When evaluating your technical infrastructure, think about the following:

  • Can you mitigate disruption to your current systems and processes while updating to AI tools?
  • Can the AI solution scale according to your evolving needs?
  • Do you have enough clean sources of data?
  • WIll staff require training or upskilling to use the new tools? (After all, “readiness also means having the right human capital to manage and evolve AI functionalities effectively,” says Cristian-Ovidiu.)

And of course, there are budgets to consider! The cost of implementing AI tools can go beyond the initial purchase or subscription fees.

Cristian-Ovidiu cautions to keep these additional costs in mind, which include:

  • Integration expenses
  • Potential downtime costs during implementation
  • Ongoing maintenance
  • Training costs for staff, and any additional infrastructure upgrades needed to support the new technology effectively.

Remember, though, that you’re investing toward long-term success, and that spending time and money on AI training might boost employee morale and improve retention in ways that are tough to track.

#3: There are many AI-powered solutions for my use case. Which one should I pick?

The market is flooded with niche-specific AI tools across numerous use cases.

So how do you compare different solutions in terms of capabilities and limitations?

Take advantage of an application’s trial versions before committing. (Of course, before you spend time doing so, you’ll want to have answered the first two questions on this list.)

Request demos to get a quick overview of the product, as well as a temperature check of the team behind it.    

Larger organizations are liable to bleed time and resources without  precise criteria for evaluation.

“Comparing AI solutions requires a deep dive into each tool’s technical merits, adaptability, and integration capabilities with our existing platforms,” says Cristian-Ovidiu.

“We evaluate vendors based on their track record for innovation, support, and security practices. It’s crucial that they not only offer a robust product but also align with our data governance standards, and that they have responsive customer service and technical support teams.”

“Consider the AI's ability to evolve as new trends emerge and how it fits into the competitive landscape,” he says. “Will this technology keep us at the cutting edge, or will it be a short-lived enhancement with limited impact?”

Questions like these can help you invest wisely in technology that offers “real, sustainable value to both the company and your customers.”

#4: How do I determine ROI?

This might be the toughest nut to crack. And if you’re a CMO who just spent a hefty chunk of Q2’s budget on a new GenAI tool, you’ll want to be able to justify that expense.  

AI ROI analysis involves synthesizing a small mountain of factors, from the complexity of integrating AI systems, to data accessibility and quality, to attribution challenges, to time saved by automating rote tasks.

Have a plan in place for calculating ROI before you sign a contract for a new tool.

You’ll probably find that effective ROI determination is an iterative process that requires continuous refinement as you gather more data, refine your models, and incorporate feedback from stakeholders.

Simply put, your AI tool’s success metrics should be based on the goals they’re meant to achieve.

So if the goal is improving customer support, says Cristian-Ovidiu, your metrics might be response time reduction and customer satisfaction scores.

The ROI is evaluated in terms of what the AI helps increase, reduce, or optimize—like “cost savings, efficiency improvements, revenue growth, or qualitative factors like enhanced customer loyalty.”

#5: What about concerns related to data privacy, security, and ethics?

Customer trust is fragile, even more so when cutting-edge AI applications are involved. Any AI tool you integrate into your tech stack should make your consumers feel safe.  

Before you procure any AI solution, consider the following:

  • Does the vendor comply with relevant data protection regulations like GDPR or CCPA?
  • Do they conduct regular security audits?
  • Can the tool handle and protect sensitive customer data?
  • Does it have security measures to safeguard against data breaches and unauthorized access?

Feel free to ask relevant questions regarding how the AI model was trained.

  • Does it mitigate biases in data and prevent discriminatory outcomes?
  • Is the algorithm fair, and can users understand and challenge AI-generated decisions?
  • Is the tool transparent about its data collection and how it influences user interactions?

It may be a good idea to appoint a person to oversee the responsible use of AII within your organization.

At the very least, develop clear policies and have procedures in place for handling any ethical dilemmas or complaints. It’s an area where your IT team and your Legal department should collaborate.

So...what next?

Once you’ve spent some time brainstorming around these 5 questions, it’s time to explore the (swiftly expanding) universe of AI martech.

When you request a product demo, you’ll come armed with your own road map, as well as pertinent areas to delve deeper into.

That’s the difference between random adoption and impactful procurement.

Manal Yousuf

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