What Are the Biggest Concerns Regarding AI?

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What Are the Biggest Concerns Regarding AI?

Here's what 22 executives who are familiar with AI said when we asked them, "What are the biggest concerns regarding AI today?"

· AI Zone ·
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To gather insights on the state of artificial intelligence (AI) and all its variants — machine learning (ML), deep learning (DL), natural language processing (NLP), predictive analytics, and multiple neural networks — we spoke with 22 executives who are familiar with AI.

We asked them, "What are the biggest concerns regarding AI today?"

Here's what they told us:


  • There’s a lot of hype and noise. Vendors latch onto terms and make it hard to distinguish what’s hype and what’s real.
  • Hype and expectations are unrealistic.
  • Many of the technologies are still green and need a lot of TLC. You need to understand what’s mature and what is not.
  • People get too excited. Stay grounded. Far from building a general-purpose robot. People overestimate how quickly we can build. Not enough thinking of legal implications for the consumer — cyber attacks and security of PII.
  • People have concerns that AI will take away jobs but that’s a misconception. AI will allow us to focus on higher value things. What job tasks do people not want to do? There’s a potential for a lot to be done with AI — a lot of hype. We have to moderate our industry. Know how to apply AI in the right way. Skills are lacking.
  • Client misperceptions over what is possible today. Data sovereignty and information security issues.
  • The risk that AI becomes so competent and their goals are not aligned with ours. Loss of credibility due to unrealistic expectation setting.


  • Amazon and Google are hoarding data. Privacy and data security come into play. It’s interesting that the government is precluded from collecting information on individuals that private companies have been collecting for years.
  • Who decides the rules that apply to a car when it’s approaching a pedestrian? How do you value the life of the occupants of the car versus the pedestrian? Ultimately, AI will outsmart humans. Will it have its own agenda and be self-aware?
  • We see privacy, security, and accuracy as primary concerns. AI can be used to improve efficiency and supplement current operations, but AI is yet to be proved 100% accurate for strategic decision-making. Organizations focusing on AI solutions need to also understand the importance of governance around AI solutions. We also believe that organizations will have to grow or attract people with new skills.
  • AI and ML tools, open-source libraries, and resources are becoming widely available and can be leveraged by black-hat hackers as well. We’ll likely be seeing more malware families and variants that are based on such tools and capabilities. Artificial intelligence can enable hackers to try and engineer malware that will aim to bypass or challenge next-gen security solutions. That will put these solutions to the test and will enable testers and evaluators to better differentiate between vendors, their expertise, and know-how in the implementation of AI to cyber security.


  • It’s evolving very quickly. Companies need to understand what AI can do for their business and identify a small business case to get started.
  • Cost and GPUs are not cheap. As more companies adopt, the price will come down. Commoditized high-level sensors.
  • I see AI like mobile and the internet. When they came out, they were transformational over the next 10 years and integrated into people’s lives. The same will happen with AI, possibly faster, with voice recognition and image recognition expected.
  • Just start running and learning. Invest wisely in solving key business problems. Be able to see the business value you are providing.
  • A skill I think will be increasingly important is understanding the data modeling — understanding how that underlying data, structured or unstructured, will be used to teach whatever AI platform you have. Anyone that works in this area should obviously know the platforms, but they should also have a strong background in data.
  • Companies’ ability to make the digital transformation. Identify what makes the most sense to work on. You must automate or you will not be happy with the end result.

What are your biggest concerns with the state of AI today?

Here’s who we talked to:

  • Gaurav Banga, CEO, and Dr. Vinay Sridhara, CTO, Balbix
  • Abhinav Sharma, Digital Servicing Group Lead, Barclaycard US
  • Pedro Arellano, VP Product Strategy, Birst
  • Matt Jackson, VP and National General Manager, BlueMetal
  • Mark Hammond, CEO, Bonsai
  • Ashok Reddy, General Manager, Mainframe, CA Technologies
  • Sundeep Sanghavi, Co-founder and CEO, DataRPM, a Progress Company
  • Eli David, Co-Founder and Chief Technology Officer, Deep Instinct
  • Ali Din, GM and CMO, and Mark Millar, Director of Research and Development, dinCloud
  • Sastry Malladi, CTO, FogHorn Systems
  • Flavio Villanustre, VP Technology LexisNexis Risk Solutions, HPCC Systems
  • Rob High, CTO Watson, IBM
  • Jan Van Hoecke, CTO, iManage
  • Eldar Sadikov, CEO and Co-founder, Jetlore
  • Amit Vij, CEO and Co-Founder, Kinetica
  • Ted Dunning, PhD., Chief Application Architect, MapR
  • Bob Friday, CTO and Co-founder, and Jeff Aaron, VP of Marketing, Mist
  • Sri Ramanathan, Group VP AI Bots and Mobile, Oracle
  • Scott Parker, Senior Product Marketing Manager, Sinequa
  • Michael O’Connell, Chief Analytics Officer, TIBCO
ai, deep learning, machine learning, nlp, predictive analytics, privacy

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