Getting Smart About Artificial Intelligence

Getting Smart About Artificial Intelligence

Five Best Practices for Diving in

Executive Summary

Artificial intelligence (AI) is no longer a futuristic, sci-fi trope. After years of development, AI technologies—including machine learning (ML), natural language processing (NLP) and computer vision—are transforming organizations and freeing up employees to do higher-value work. For marketers and advertisers, AI is already disrupting core functions, including ad targeting, media buying, content creation and propensity modeling. But getting started can be difficult. There’s a dizzying array of solutions and many potential pitfalls. This report highlights five best practices for marketers as they explore the complex AI ecosystem.

What factors should marketers consider before implementing AI?

Marketers should have a clear vision of how AI will solve a specific business problem, then implement a realistic strategy to achieve that goal. The decision to build or buy AI capabilities depends on the resources available, the problem that needs to be solved and the company’s culture. Marketers must also be prepared to invest in refining their systems and committing for the long haul.

Are certain skill sets required to successfully manage AI technologies?

The AI ecosystem can be complex and confusing, and AI projects often require unique skill sets that may entail hiring new workers or retraining employees. Ultimately, AI is a digital transformation that is forcing marketers and technologists to work more closely together.

What data is necessary for successful AI projects?

Good data is the bedrock of AI modeling. If a project doesn’t have the right data, the results will be less than optimal. However, not having perfect data at the outset shouldn’t prevent marketers from getting started.

Should marketers tell their customers they are using AI?

Because AI systems can crunch through vast amounts of personal data from different sources, transparency and trust are becoming increasingly important. Organizations must ensure they are using the technology in responsible ways and clearly communicating how it may affect their stakeholders.

WHAT’S IN THIS REPORT? This report offers marketers five best practices for using artificial intelligence and machine learning in their operations.

KEY STAT: Some of the most common ways businesses are preparing to use AI include learning from early adopters, seeking outside advice and ensuring staff has the right skills.

Here’s what’s in the full report

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25charts

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18expert perspectives

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Table of Contents

  1. Executive Summary
  2. AI Grows in the Enterprise
  3. Best Practice No. 1: Define the Problem First
  4. Best Practice No. 2: Pick the Right Tools for the Job
  1. Best Practice No. 3: Convene the Experts
  2. Best Practice No. 4: Bring Together the Right Data
  3. Best Practice No. 5: Future-Proof the System
  4. Key Takeaways
  1. eMarketer Interviews
  2. Read Next
  3. Sources
  4. Media Gallery

Charts in This Report

Interviewed for This Report

Raj Balasundaram
Emarsys
Vice President, Solutions and Strategic Services
Interviewed December 21, 2018
Paul Bannister
CafeMedia
Executive Vice President, Strategy
Interviewed December 6, 2018
Arnab Bhadury
Flipboard
Data Scientist and Machine Learning Engineer
Interviewed December 6, 2018
Winston Binch
Deutsch North America
Chief Digital Officer
Interviewed December 11, 2018
Anusha Dandapani
NYU School of Professional Studies
Adjunct Faculty
Interviewed December 10, 2018
Sonjoy Ganguly
Madison Logic
Chief Product Officer
Interviewed December 27, 2018
Damian Garbaccio
Nielsen
Executive Vice President, Advertiser Direct and Nielsen Marketing Cloud
Interviewed December 21, 2018
Jim Hertzfeld
Perficient
Chief Strategist, Digital
Interviewed December 21, 2018
Christine Livingston
Perficient
Artificial Intelligence CoE Director and Chief AI Strategist
Interviewed December 21, 2018
Tatiana Mejia
Adobe
Group Product Marketing Manager, Adobe Sensei
Interviewed December 13, 2018
Christian Monberg
Zeta Global
CTO
Interviewed December 18, 2018
Huanlei Ni
Goodway Group
Director of Technical Product Management
Interviewed December 19, 2018
Ganesh Padmanabhan
Cognitive Scale
Vice President, Head of Business Development and Worldwide Marketing
Interviewed December 17, 2018
Armita Peymandoust
Salesforce
Vice President, Product Management, Analytics and Einstein
Interviewed December 19, 2018
Ravi N. Raj
Passage AI
Co-Founder, CEO
Interviewed November 30, 2018
Mazdak Rezvani
Chatkit
Founder, CEO
Interviewed December 13, 2018
Ryan Steelberg
Veritone
President
Interviewed December 27, 2018
Dinesh Gopinath
Kantar Analytics
Head of Product and Data Strategy
Interviewed December 18, 2018

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authors

Victoria Petrock

Contributors

Ross Benes
Analyst
Paul Briggs
Senior Analyst
Caroline Cakebread
Junior Analyst
Rahul Chadha
Senior Analyst
Chris Keating
Research Director
Nicole Perrin
Principal Analyst
Jillian Ryan
Principal Analyst
Tracy Tang
Senior Researcher