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Opportunities for AI

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Opportunities for AI

Reduction of operating costs, automation of repeatable processes, and around call centers and improving customer service.

· AI Zone ·
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Bias comes in a variety of forms, all of them potentially damaging to the efficacy of your ML algorithm. Read how Alegion's Chief Data Scientist discusses the source of most headlines about AI failures here.

To gather insights on the state of artificial intelligence (AI), and all of its sub-segments — machine learning (ML), natural language processing (NLP), deep learning (DL), robotic process automation (RPA), regression, et al, we talked to 21 executives who are implementing AI in their own organization and helping others understand how AI can help their business. We began by asking, "Where do you see the biggest opportunities in the implementation of AI?" Here's what they told us:

Reduce OpEx

  • Manufacturing and supply chain because they are pure cost centers. Reduce operational costs with the trade. Next automated truck driving. 
  • Big opportunity in the business benefits and all that and the concept of data for good. Leverage AI and analytics with data to change society and bring awareness to world crisis’s, predicting areas of risks for floods, landslides, tornadoes to better predict risk and save lives. From a personal and corporate standpoint, we’re recognizing the power AI can bring good to society. Solve issues that can be brutally terrible for a community, area or people. 
  • The increasing adoption of ERP workloads in the public cloud is leading to faster consumption of innovation. Innovative areas like artificial intelligence, machine learning, and natural language interfaces are gaining the most traction. 
  • For our customers, truly conversational AI will change the game in terms of how they interact with their customers. Imagine being able to get in the car and have a human-like conversation with the assistant to make a dinner reservation at a restaurant you like based on your meeting calendar. Assistants are prevalent now but advancing toward a true dialogue will create immense opportunity. There is also a lot of opportunities for companies to use AI internally for workforce productivity and cost reduction. Specifically, wherever AI may be used to replace laborious, manual processes, companies can reap great efficiency benefits and improve worker conditions by freeing them up from doing mundane tasks and instead provide greater opportunity for more meaningful work. Further, AI analytics capabilities are becoming more robust, delivering valuable insights into consumer preferences, behavior, sentiment, and intents that can be used to deliver differentiated experiences throughout the customer lifecycle. 
  • When you’re an enterprise looking to improve the bottom line and improve business processes. Wring cost out of business. All outbound stuff makes apps so much better see what you’re doing and interject on how you can make this easier. I can notify you and then do the transfer for you and tell you. Interactions with intelligence is initiated by humans is the applications will initiate more of the applications and do stuff for you. Percent of success will increase.


  • Security, information classification and retrieval, and automation will be the biggest opportunities within the next 5-10 years. A few of the industries that this will be most important to are cybersecurity, fraud detection, call center and help desk automation, medical imaging and diagnosis, personal assistants, legal compliance, and consumer relations. 
  • The more complex, distributed and hybrid is the IT environment and the more critical are the business processes for the enterprise, the biggest is the opportunity for AIOps and FixStream to help enterprise customers. If enterprises have a very large, dynamic IT environment spanning on-prem and cloud deployment, if they have eCommerce, or Oracle/SAP ERP based applications like Order-to-Cash, Procure-to-Pay, Supply-Chain-Management, etc. they will not be able to effectively manage them, unless they deploy AIOps.

Customer Service

  • Depends on the horizon. Short-term a lot of business value coming out of chatbots – revolutionize support. AI is very good at fixing IVR. Reduce cost and improve quality. Long-term conversational AI outside of text to voice that’s the next frontier. Don’t underestimate conversational AI from a personal point of view. A lot of people in the world are very lonely and will appreciate social AI. Elderly care very expensive with staff. Require volume in conversation. Can provide stimulus in many other ways. Healthcare will be a huge area for AI. Will change what’s going to be a good doctor in the future. 
  • One of the biggest opportunities is the implementation of AI in digital communications (which is the path we’re on). Digital communications have the potential to feel like actual human conversations. With AI, there is an opportunity to do much more targeted communications based on a whole host of things that we know about a person which are current advantages that we have with real 1:1 human relationships. The same is possible digitally. AI is the key to unlocking that.


  • Going to become ubiquitous - more common and pedestrian. Just another way to do programming. Not doing the code the same way. Doing example and making decisions that are hard to write computer code to do.
  • Seem to be so many. Every industry there is an opportunity. We will not run out of opportunities. Incremental growth opportunities for companies. You can start with a small thing and augment and then use ML over time. We see fraud detection, resource assessment, forecasting, and recommendations.
  • The upside is infinite go from three to 100. Achieve the goals your business wants to leapfrog the competition and become branded as digital-first.
  • The huge opportunity we don’t know what we can achieve yet. Automotive is big with autonomous vehicles. By 2030 every second car will be automated. Business model transformation and allowing for completely new business models. Auto manufacturers don’t need to be worried they sell more car but who they sell to will change.
  • It’s a journey in which we’re dealing with tremendous innovation. Legacy humans don’t have the skillset to deal with the current technical solutions. The problem is there is a pace of innovation. Adapt to where humans can make use of it. Empower humans on the job to be more effective at what they do.
  • All about sensors. As the price of mem sensors get cheaper opportunities for instrumentation are burgeoning. Easier to put more sensors on any kind of tool to make sense of the data.
  • One of the biggest opportunities we see for the audio industry is the ability to use AI to inform and develop a new type of business for content creators, giving them the opportunity to monetize as well as extend the shelf life of their audio content.
  • AI holds great promise for improving man’s quality of life. Certainly, the most popular use case is self-driving cars. Senator Gary Peters from Michigan believes that traffic deaths could be reduced by 90% using AI. Another significant opportunity is in drug discovery and the treatment of chronic diseases such as cancer and Alzheimer’s. Pattern recognition is already being applied to pathological images to improve clinical outcomes through more accurate and timely treatment, and improved search functions are helping pharmaceutical companies identify new compounds and speed drugs to market.
  • Hopefully, AI will provide better and quicker diagnosis for diseases and more immediate impact on patients. Autonomous driving is another exciting venture, as it will make the average person’s life much easier. In IT, the biggest opportunity is for a self-healing network that can correct and fix issues before a user even notices will be a profound development.

Here's who we spoke to:

  • Assaf Gad, Vice President and Strategic Partnerships, Audioburst
  • Tyler Foxworthy, Chief Scientist, DemandJump
  • Patric Palm, CEO, Favro
  • Sameer Padhye, CEO, FixStream
  • Matthew Tillman, CEO, Haven
  • Dipti Borkar, V.P. Product Marketing, Kinetica
  • Ted Dunning, Chief Application Architect, MapR
  • Jeff Aaron, VP Marketing and Ebrahim Safavi, Data Scientist, Mist Systems
  • Dominic Wellington, Global IT Evangelist, Moogsoft
  • Dr. Nils Lenke, Director, Corporate Research, Nuance Communications
  • Mark Gamble, Senior Director of Product Marketing, OpenText
  • Sri Ramanathan, Group Vice President of Mobile, Oracle
  • Sivan Metzger, CEO and Co-founder, ParallelM
  • Nisha Talagala, CTO and Co-founder, ParallelM
  • Stuart Feffer, Co-founder and CEO, Reality AI
  • Sven Denecken, SVP Head of Product Management, SAP S/4 Hana Cloud
  • Steve Sloan, Chief Product Officer, SendGrid
  • Simon Crosby, CTO, Swim
  • Liran Zvibel, CEO and Co-founder, WekaIO
  • Daniel DeMillard, A.I. Architect, zvelo
  • Your machine learning project needs enormous amounts of training data to get to a production-ready confidence level. Get a checklist approach to assembling the combination of technology, workforce and project management skills you’ll need to prepare your own training data.

    artificial intelligence ,machine learning ,deep learning ,natural language processing ,robotic process automation ,interview

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