Trend #3 Artificial Intelligence (AI) : Top 25 Digital Startup ideas and technologies for 2017

Enterprises large and small continue their digitization journey, and CEOs, CXOs and CIOs want be at the forefront of their corporate digitization initiatives. Among the most promising technology trends is Artificial Intelligence.

Artificial intelligence (AI) is the intelligence exhibited by machines or software. It is also the name of the academic field of study which studies how to create computers and computer software that are capable of intelligent behavior.” – Wikipedia

The potential for artificial intelligence has been imagined by science fiction writers and Hollywood directors for decades. The business world is finally getting serious about the disruptive potential of AI. Technologies with thought provoking names like Deep Blue from IBM, DeepMind from Google or Microsoft’s Chatbots are going beyond press-mentions and vaporware to solving real world problems.

Recognizing the significance of the trend, the White House released a new report on the ways that artificial intelligence will transform our economy over the coming years and decades. (link: Artificial Intelligence, Automation, and the Economy)

Image credit: Charis Tsevis

Applications of AI can range from high-skill tasks such as recognizing cancer in x-ray images to lower-skill tasks such as recognizing text in images. Likewise, the AI tools and technologies applied to solve real-world problems can range from machine learning, big data, analytics to use of intricate algorithms and computing techniques.

Many industry professionals refer to a large swath of AI technologies as “Augmented Intelligence,” stressing the technology’s role as assisting and expanding the productivity of individuals rather than replacing human work. Thus, based on the biased-technical change framework, demand for labor will likely increase the most in the areas where humans complement AI-automation technologies. For example, AI technology such as IBM’s Watson may improve early detection of some cancers or other illnesses, but a human healthcare professional is needed to work with patients to understand and translate patients’ symptoms, inform patients of treatment options, and guide patients through treatment plans. Shipping companies may also partner workers who pickup and deliver goods over the last 100 feet with AI-enabled autonomous vehicles that move workers efficiently from site to site. In such cases, AI augments what a human is able to do and allows individuals to either be more effective in their specialty task or to operate on a larger scale.

AI substitute for “Thinking Jobs”

In a recent HBR article, Megan Beck and Barry Libert explain “There are just a lot of things that machines can do better than human beings, and we shouldn’t be too proud to admit it.  Many skilled jobs follow the same general workflow:

  1. Gather data
  2. Analyze the data
  3. Interpret the results
  4. Determine a recommended course of action
  5. Implement the course of action

We can look at any number of occupations to see that this holds true.  Doctors perform tests, analyze the results, interpret the results to make a diagnosis, plan a course of treatment, and then work with the patient to make this treatment plan a reality.

Financial advisers gather and analyze data about their clients and potential investment vehicles, interpret the implications given a variety of factors such as risk tolerance, recommend an investment strategy, and help their clients carry this strategy out over time.”

Artificial Intelligence Opportunities

Artificial Intelligence is not a single technology, but rather a collection of technologies that are applied to specific tasks. Therefore, the opportunities in AI are varied:

  • Machine learning applications – Emerging opportunities include application of AI frameworks and machine learning to automate problems in different domains.  An illustrative list of ideas entrepreneurs are working on:
    • Medical applications – automating transcriptions using voice recognition, reading and tabulating X-rays, AI databases aiding decision making by doctors and Surgeons.
    • Financial analytics and forecasting – personalizing financial services through analytics-driven recommendation engines, robo-advisory services in the wealth management
    • Applying machine learning to identify images or videos (starting to be researched by security agencies, Immigration and customs departments)
    • Making Smarter Assistants – Entrepreneurs and startups are seeking to build an artificially intelligent assistant better than Siri, Alexa and Cortana
    • Automating advertisements and analysis of Ad’s
    • Fraud detection and prevention – automated fraud detection, as well as anti-money laundering and anti-terrorist financing compliance monitoring; and
    • Bots, and automated tools to aid cyberdefense and cyber security, predictive cybersecurity monitoring and response systems.
  • Data mining and analysis. The challenge is to formulate and ask intelligent questions using data that can provide us with answers, predictions and recommendations. Entrepreneurs are developing ideas to aid in investigation of large, disparate data sources and designing algorithms to train systems to recognize patterns.
  • Robotics – Design robots and industrial automation to enable them to take decisions by themselves. A popular example is the emergence of self-driving cars and Drones.
  • AI research and development – This includes improvements to machine learning algorithms and domain specific application of the algorithms.
  • AI Software development, design, program management and testing. Some of the development could involve customizing existing solutions or leveraging commercial platforms like IBM’s Watson.
  • Education and training – Universities and technical schools around the world continue to introduce courses and training programs on AI. Opportunities for universities and corporate trainers include
    • Train the trainer – Including PhD and masters level programs in AI, Machine learning etc
    • STEM (Science, Technology, Engineering and Math) – Including motivating young students towards STEM education and re-education of existing workforce to focus on machine learning and AI, and good math skills
    • Corporate training opportunities focused on vendor tools and technologies

Government and Social Policies

The White House report adds: Advances in Artificial Intelligence (AI) technology and related fields have opened up new markets and new opportunities for progress in critical areas such as health, education, energy, economic inclusion, social welfare, and the environment. In recent years, machines have surpassed humans in the performance of certain tasks related to intelligence, such as aspects of image recognition. Experts forecast that rapid progress in the field of specialized artificial intelligence will continue. Although it is unlikely that machines will exhibit broadly-applicable intelligence comparable to or exceeding that of humans in the next 20 years, it is to be expected that machines will continue to reach and exceed human performance on more and more tasks. Although it is difficult to predict these economic effects precisely, the report suggests that policymakers should prepare for five primary economic effects:

  • Positive contributions to aggregate productivity growth;
  • Changes in the skills demanded by the job market, including greater demand for higher-level technical skills;
  • Uneven distribution of impact, across sectors, wage levels, education levels, job types, and locations;
  • Churning of the job market as some jobs disappear while others are created; and
  • The loss of jobs for some workers in the short-run, and possibly longer depending on policy responses.

It is likely that governments and policy makers around the world will review the viewpoint from the White House to define their own policies.


AI : Startup Solutions in the news

  • AI In Financial World –Wall Street’s Big Brother: The AI Software Goldman Sachs And Steve Cohen Are Using To Track Traders – When Tim Estes, 37, created Digital Reasoning as a twenty-one year old with a philosophy degree from the University of Virginia, his startup aimed to use software to bridge mathematics with language and understand human behavior. Sixteen years on, Estes’ language-learning technology is used by a who’s who roster of Wall Street’s most scrutinized firms as they rein in employees and avoid the multi-billion dollar regulatory fines that have plagued the industry since the crisis. – Forbes
  • AI in Manufacturing – GE acquires to deepen its machine learning stack – GE Digital today announced that it has acquired, a machine-learning powered service that helps businesses find patterns and trends in their vast data stores. At first glance, that may seem like an odd acquisition for a company like GE. It’s important to keep in mind, though, that with Predix, GE already offers its customers a service that focuses on helping them monitor their equipment, whether that’s an industrial tool or an aircraft engine, and predict issues based on the monitoring data.
  • At Sundar Pichai’s Google, AI Is Everything—And Everywhere – -“Building general artificial intelligence in a way that helps people meaningfully—I think the word moonshot is an understatement for that,” Pichai says, sounding startled that anyone might think otherwise. “I would say it’s as big as it gets.”

Lead Author: Mohan K

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