Top 4 AI Implementation Challenges and How to Address Them

Tara Kelly on May 25, 2017

Tara Kelly, CEO of SPLICE Software, believes AI can help business leaders improve CRM, if 4 main challenges are overcome. She also discusses how to overcome the challenges of AI so that it can be used for an enhanced customer relationship.

The digital revolution transformed marketing, giving marketers new tools to communicate with customers, fresh ways to measure results and data-driven strategies to continuously improve the customer experience (CX). Artificial intelligence (AI) is poised to power the next epoch in marketing.

AI isn’t a separate phenomenon from the digital revolution; it’s the logical extension of the proliferation of data, evolution of algorithms and exponential growth of computing power. Marketers and consumers are already using AI in scenarios as diverse as programmatic ad buying and asking their Alexa device to order more coffee pods.

But these applications barely scratch the surface of AI’s potential, and in the coming years, AI will change how consumers interact with brands and how marketers practice their craft in more fundamental ways. The potential is enormous, but, as in any revolution, there will be challenges along the way. Here’s a brief look at four of them and thoughts on how to address each one:

  1. Data quality: The success of an AI solution is directly dependent on the quality of the data that fuels it. Before marketers can fully benefit from AI, they’ll need to ensure that their data passes the “sniff test.” Is it up to date? Does it accurately reflect the customer’s relationship with the company? For some marketing teams, a comprehensive data cleanup project will be the first step in their AI journey.
  2. Data intake: In addition to starting with high-quality data, it’s essential that a marketing AI solution is capable of taking data in quickly (if not in real time) and applying it correctly. Think of how map applications work: an accurate depiction of possible routes is the starting point. The most useful apps are able to take in new data (construction, new roads, traffic congestion, etc.) and provide real-time information.
  3. Human assist factor: AI isn’t designed to replace humans; the goal is to make appropriate use of data and automation elements (e.g., voice talent, SMS messaging, etc.) so marketers can engage in strategic rather than rote tasks. That’s why it’s important to make sure the AI solution has an iterative human assist factor that validates when people get better results, allowing for smarter AI application.
  4. Question quality: It’s important to remember that AI will only answer questions that are directly asked, so users must carefully consider phrasing, applying intuition to make sure they’re asking the right questions. For example, people who are looking for cashback mortgages may actually be seeking debt consolidation assistance. The AI solution won’t know that intuitively, but a human should.

AI has many exciting implications for the practice of marketing. People won’t be replaced; instead, they’ll be freed from mundane tasks to take on strategic work that requires their intuition and marketing savvy. Like the digital revolution before it, the rise of AI will be utterly transformative. The technologies associated with AI, when applied correctly, have massive potential to improve marketing operations.

But it’s important for marketers who want to capitalize on AI’s potential to prepare their data ahead of time so that it yields optimal results. It’s also crucial to find an AI solution that can take in new information quickly and apply it in ways that provide customers with the best possible experience. And it’s essential for the people who are working with AI to apply the human element judiciously.

When marketers embrace the possibilities of AI, vet their data, find the right solution and understand the key role they play in an AI environment, they’ll be prepared to reap the benefits of the next big trend in technology. More importantly, they’ll be in a better position to personalize outreach, build long-term relationships and consistently deliver a stellar CX at every phase of the journey.

Topics: Strategy, API, Automation