Artificial intelligence can have a transformative effect on marketing, making campaigns more personalized, productive and predictive.
But the technology comes with very real disadvantages and limitations.
You’ll currently need to rely on individual solutions to perform certain AI-powered marketing tasks.
For instance, Narrative Science and Automated Insights provide natural language generation (NLG) capabilities, an AI-powered technology used to scale content creation.
Albert uses AI to optimize paid campaigns.
And solutions like Cortex, Acrolinx and Skyword offer various ways to personalize and optimize content marketing.
With no one-size-fits-all solution, but plenty of powerful specialized tools, it’s important for marketers to clearly understand the real possibilities—and limitations of—artificial intelligence.
To help accomplish that goal, six artificial intelligence experts told us what they see as the biggest limitations in AI today.
“Reliable sentiment analysis (i.e. figuring out if a sentence is happy, sad or sarcastic) is really hard for artificial intelligence, along with reliable sentence parsing. Visually recognizing a teacup reliably is challenging for current machine vision algorithms. Folding laundry is another incredibly hard task for artificial intelligence powered robots. The human intuitions underlying what data to look for and what questions to ask are some of the biggest limits now.
“Another limitation is the ability to operate on very small amounts of evidence or data. For example, if you look at a lot of the bioinformatics applications, each piece of data is a patient’s DNA. In those cases you don’t have a lot of data, so it’s very difficult for researchers to figure out which genes correlate with illness.
“Another difficulty for AI is trying to optimize for multiple dependent outcomes concurrently. Let’s say you want to optimize two conversion rates simultaneously; that becomes very complex and difficult very fast. Imagine you’re A/B testing for a landing page, and there’s another algorithm that varies the ad creative that draws people to the landing page in the first place. The way to do that now is to do both independently of each other, because doing both at once quickly becomes computationally intractable.” — Pawan Deshpande (@idlivada), Head of ModelOps at @DominoDataLab & founder at @Curata
“Luckily, there are lots of applications where AI can be used to empower humans rather than replace them. When AI is used to crunch data to come out with recommendations for instance, it still provides a lot of value if these recommendations are ‘right’ only 80% or 90% of the time—because humans can quickly determine the correct actions from the incorrect ones.” — Guillaume Decugis (@gdecugis), CEO of @Linkfluence, Cofounder, Scoop.it
“In marketing, the disparate disconnected systems that form the marketing stack can be a major obstacle in the first of these. Historically, you’ve had different platforms for content creation, analytics, content hosting, demand generation, sales, etc. Consequently, there is a lot of data loss. When you lose the connection between data points, you are only able to assess some behavior in aggregate versus individual use cases. This also means delays in gathering the data so you can’t act in real time or near real time.
“In our particular space, that meant marketers didn’t have the content, usage data and channel data—and couldn’t access direct results. We’ve tried to tackle this by creating an integrated platform with a range of data inputs that tie out to a single user.” — Tom Gerace (@tomgerace), CMO EquiLife, Founder, Skyword
“Limitations in artificial intelligence will also stem from the degree of precision with which technologists are able to replicate human ‘intelligence’ and decision-making.” — Or Shani (@or_shani), CEO, Albert
“And therein lies the second, more important challenge, at least from the perspective of an entrepreneur like myself. Many times clients have very strong opinions on AI, maybe they have done some proof of concept already and they think they are experts. Or, they are ‘armchair experts’ based on the latest TED talk they've seen and have highly unrealistic expectations when it comes to AI. AI has some very powerful, proven use cases for marketing and beyond, but it is important that customers, vendors, providers, consultants and everybody else stick to these value-adding, working applications rather than building castles in the sky and setting unrealistic expectations.
“I am not saying we shouldn't dream and be visionary when it comes to AI for marketing, but I think it is just as important that we deliver real results to prove the power of this technology.” — Andre Konig (@AndreMKonig), Cofounder, Opentopic
These disadvantages may lead you to believe AI is negatively affecting marketing. Nothing could be further from the truth.
These are very real limitations, to be sure. But AI also holds great promise in the industry.
AI is beginning to impact every aspect of marketing, including:
In fact, AI is going to bring more than $2 trillion in value to marketing and sales alone by increasing revenue or decreasing costs.
Today, savvy marketers are finding new ways to increase performance using accessible and affordable AI tools.
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