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© 2019 eMarketer Inc.

Getting Smart About AI: Five Best Practices for Diving In

Victoria PetrockPrincipal Analyst

February 21, 2019


Key Questions:

How are marketers currently using AI?What resources are available to help

you get started?What should you be thinking about to

position your project for success?


What is Ar tificial Intelligence?

The ability of machines to emulate human thinking, reasoning and decision-making


AI is a catch-all for many different things

Natural language processing

Recommender systems

Computer visionNatural language generation

Neural networks

Deep learningMachine learning Virtual digital

assistants

Predictive analytics

Robotic process automation


$5.4

$105.8

2017 2025

Worldwide market for AI software ($ billions)

Business leaders worldwide are bullish about AI

Source: Tractica, 2018


69%

84%

86%

90%

0% 20% 40% 60% 80% 100%

Job creation

Innovation

Productivity

Growth

Series 1They believe AI will have a positive effect on business operations

Source: Economist Intelligence Unit, 2018


Marketers are using AI for four core activities

Segmentation

Messaging

Media activation

Analytics


No. 1: Define the problem first

Know what AI can and cannot do

Clearly define goals

Don’t try to do too much

Link AI to business outcomes

Create a clear strategy and road map

Image Credit: geralt/Pixabay.com


43%Professionals who said lack of clear strategy was a top barrier to AI adoption:

Source: McKinsey, 2018

Just 18% said they had clear strategies in place


“If you can’t clearly define the problem, you shouldn’t even be starting.”


No. 2: Pick the best tools for the job

Open-source, low-level machine-learning frameworks

Higher-level commercial applications

Point and turnkey solutions

Software development platforms and application programming interfaces (APIs)


There are many routes to AI

Build in-house capabilities

Buy or license from third parties

Partner with academia or businesses

Acquire companies

Crowdsource AI capabilities


Top 3 things tech professionals are doing to get started with AI

Learning from early adopters

30%

Seeking advice from third parties

Training existing staff

26% 23%

Source: UBM Technology Group, 2018


“Generally speaking, you’ll need a mix of three sets of skills: People who have AI product knowledge, businesspeople with marketing expertise and data engineers.”

No. 3: Assemble the right team


There’s currently a severe shortage of AI talent

Data scientists

Data engineers

AI researchers

Software developers

UE designers

Change management experts


No. 4: Bring the right data together

Image Credit: geralt/Pixabay.com

Break down data silosFind the right dataEnsure data is cleanPut proper consents in

place


15

12

10

0 5 10 15 20

2019

2018

2017

Series 1Average number of data sources used:Marketers are using more data than ever

Source: Salesforce, 2018


Data silos are a huge problemfor many companies

Breaking down these silos and improving the data flow are just as important as having the right data.


“There’s a phrase, ‘think big, start small, act fast,’ and there’s a good start in using the data you already have.”

But don’t wait for your data to be perfect


No. 5: Future-proof the system

Cultivate C-level support

Maintain ethics and transparency

Carefully manage change

Develop meaningful measurement

Budget for trial and error

Evolve with the times


Key TakeawaysThe AI ecosystem is dizzyingly complexWithout humans, there is no AISuccessful projects require top-level supportAI experts are in short supply

It’s getting easier to work with AI dataTransparency and ethics are critical

AI projects require continuous care and feeding

getting smart about ai - emarketer...© 2019 emarketer inc. key questions: how are marketers...

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