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Artificial intelligence: 7 Common Mistakes Even Experienced Tech Execs May Make

Sharon Tal and Marc Gruber, authors of Where to Play, cite seven common mistakes based on more than a decade of research working with tech startups


News provided by

Sharon Tal and Marc Gruber

Dec 06, 2017, 19:02 ET

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HAIFA, Israel, Dec. 6, 2017 /PRNewswire/ -- Technion -- McKinsey & Company* estimates major technology companies spent between $20 billion and $30 billion on AI in 2016.  AI's ubiquity is real as exemplified by Apple's Siri, Amazon's Alexa, and Google's Assistant. Yet, we are probably in the buggy-whip era of digital assistants.  Each include artificial intelligence, but expect that AI capabilities in personal assistants will soon eclipse today's capabilities. 

Plus, AI will likely automate customer service with human-like intelligence. Right now, artificial intelligence is used to make snap trading decisions in response to news reports.  It could write this press release. (It didn't.) 

Companies are rushing to integrate AI into products and services.  In the rush, it is likely many companies – especially entrepreneurial companies - will make costly mistakes. 

Extrapolating from more than a decade of research of entrepreneurial companies, Sharon Tal and Marc Gruber, authors of Where to Play, have cited seven common mistakes that were made by even the most successful executives:

  1. Falling in love with the first AI solution (make sure to create a choice set of business options before you settle on one) 
  2. Staying in your neighborhood -- Search outside your current business and beyond your current customers for new applications and markets (search distantly, in other market domains, create a varied set of options)
  3. Searching for the 'perfect' opportunity (there is no such thing, they all have pros and cons, need to accept this and be aware of the downsides)
  4. Rationalizing intuition (perform a systematic, comprehensive assessment and apply a structured decision making framework. Involve other team members.)
  5. Suffering from paralysis by analysis (at some point you need to choose, accept uncertainty, it's part of the innovation game)
  6. Putting all the eggs in one basket (mitigate your risk, design a smart portfolio of backup and growth options that you keep open)
  7. Assuming there is no technical debt (evaluate if using the AI technology today, may cost you later on.  Moving too fast may mean you need to implement better technology later on – or today's technology can consume precious capital and human resources.)

According to Tal, "As executives become enamored and anxious about adopting AI technology, there is an increased chance for making a technology bet that can consume the assets of a company. It is critical that companies map out their opportunities, test and prove a tech integration before making a huge investment that could actually derail a company strategy."

Added Gruber, "AI has accelerated a new world of speed and adaptation for tech – where there is no time for time outs.  Managers must learn how to set a promising strategy when applying such novel technology, and at the same time stay open and agile for adaptation and change." 

Where to Play teaches entrepreneurs and innovators how to systematically identify, evaluate and strategize market opportunities by applying the Market Opportunity Navigator to make sure that an enterprise is running in the right direction. 

"A wrong move can actually derail a company strategy.  In an age of speed, companies should actually test and prove a technology's value in the market before making a big bet," Tal concluded.

About Where to Play:

Where to Play teaches you how to systematically identify, evaluate and strategize your market opportunities.  It's a practical handbook for anyone striving to commercialize new innovations.  Learn how to apply the Market Opportunity Navigator with detailed exercises and case studies, to make sure that you are running in the right direction.  Identify all your opportunities and recognize patterns and distinctions among your options to design a promising Agile Focus strategy by spreading your investment smartly over carefully selected opportunities.

About Sharon Tal

Sharon Tal is a co- founder and former executive director of the Entrepreneurship Center at the Technion, Israel Institute of Technology, and a well-recognized lecturer on marketing for high-tech startups. She gives lectures and workshops on a regular basis to students and start-ups, and serves as a mentor in many organizations that aim to help budding entrepreneurs. Sharon has vast experience in marketing, as she served as a marketing manager for firms in several industries, as well as extensive experience in strategic consulting. Her PhD research looked at market entry decisions of hundreds of startups and its consequences on firm performance and flexibility.

About Marc Gruber

A world-leading researcher in the domain of innovation, entrepreneurship and technology commercialization, Marc Gruber is Vice President for Innovation at the Swiss Federal Institute of Technology (EPFL) in Lausanne, Switzerland, where he also heads the Chair of Entrepreneurship & Technology Commercialization. He works as the Deputy Editor for the #1 empirical research journal in management, the Academy of Management Journal. He received multiple "Thought Leader" awards for his breakthrough research. Marc is actively engaged in teaching, consulting, and executive training programs in Europe, the US and Asia, and regularly acts as a jury member in start-up and corporate entrepreneurship competitions across Europe.  He has been ranked as the #1 researcher in entrepreneurship 2005-2015 http://entc.epfl.ch/team/gruber.html

*McKinsey Global Institute: ARTIFICIAL INTELLIGENCE THE NEXT DIGITAL FRONTIER? June 2017

SOURCE Sharon Tal and Marc Gruber

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