Ayn de Jesus
Ayn serves as AI Analyst at Emerj - covering artificial intelligence use-cases and trends across industries. She previously held various roles at Accenture.
Articles by Ayn
Most people may associate augmented reality (AR) with smartphone apps and video games, perhaps even Pokemon Go. But augmented reality is gaining traction in a variety of industries, including manufacturing and healthcare.
Digitally-native eCommerce businesses are used to working with their customer data in order to write copy for marketing campaigns, run PPC ads, calculate customer lifetime value, and make decisions based on core metrics within CRM dashboards.
Although it's apparent that AI development is slow-moving in the industry, food and beverage companies may be able to use AI for food processing, in particular:
Banks are in one of the best positions for leveraging AI in the coming years because the largest banks have massive volumes of historical data on customers and transactions that can be fed into machine learning algorithms. We recently completed our Emerj AI in Banking Vendor Scorecard and Capability Map in which we explored which AI capabilities banks were taking advantage of the most and which they might be able to leverage in the future.
Life sciences companies are likely to begin experimenting further with AI in their workflows in the coming years, but they face challenges in AI adoption due to strict regulations. Machine learning has a "black box" problem, meaning that it's in many cases impossible to know how a machine learning algorithm comes to its conclusions.
Artificial intelligence is changing the way healthcare networks do business and physicians perform their routine activities from medical transcription to robot-assisted surgery. Although the more mature use-cases for AI in healthcare are those built on algorithms that have applications in various other industries (namely white-collar automation), we believe that in the coming three to five years, AI solutions for healthcare will become increasingly specialized to individual use-cases.
The International Energy Agency’s latest annual gas market report, Gas 2018, estimated that global gas demand could reach more than 4,100 billion cubic meters (bcm) in 2023. This is an increase from 3,740 bcm in 2017. Greater gas demands mean more oil rigs, and the machines on these rigs break down.
According to McKinsey, global gas demand is expected to reach 4,503 billion cubic meters (bcm) in 2035, showing a more than 1% annual growth from 3,736 bcm in 2017. Asia is expected to be the biggest consumer of the resource at 47%, followed by the rest of the world (24%), the Middle East (16%), and the United States (14%).
The healthcare industry is perhaps second only to finance when it comes to the sheer amount of historical data available for use with artificial intelligence. Data from EMRs, insurance claims, clinical trials, and drug research and development can all be pulled into a machine learning algorithm to generate insights on patient behavior, patient risk, and effective treatments for a variety of conditions, among a variety of others.
McKinsey estimated that embarking on digital transformation to restructure value chains and drive R&D innovation across the pharmaceutical industry could be worth $50–150 billion of earnings before interest, taxes, depreciation, and amortization. In particular, machine learning is likely to continue finding a place in the pharmaceutical industry. Pharmaceutical companies have found applications for machine learning ranging from drug discovery to clinical trial retention.
The State of AI in the Asian Pharmaceutical Industry
AI seems to be making its way into the pharmaceutical space in Asia over the last two or three years, particularly in China and Japan. For the most part, the companies offering or using AI for drug discovery are just starting to acquire funding and talent. XtalPi seems to have the highest density of talent with a decent likelihood of being able to work with machine learning.
Sensors and mobile devices are in many ways working with AI software for business intelligence purposes in a few industries, including insurance and oil and gas. In the healthcare space, mobile devices and wearables allow patients to receive information on possible diagnoses for their symptoms and to monitor metrics such as their heart rate.
Accenture reports that in 2017, the 16 top biopharmaceutical companies in the world had an aggregate global revenue of $428 billion, which was nearly half the global pharmaceutical market by net sales. The report also revealed a shift to specialty drugs for hard-to-treat diseases.
Accenture forecasts that the retail industry could grow operating profits to $2.95 trillion by 2025. We've covered AI in retail extensively on Emerj, and in this report, we dive into the Asian startups that are offering AI solutions to retailers. Asian AI vendors seem to offer retailers solutions for marketing, sales, operations, and making purchases easier, among other areas.
Forrester estimated that online sales in Western Europe will grow at an average of 11.9% annually until 2022. Over this period, 21% of non-grocery retail sales will be online. We see AI as continuing to find its way into the retail industry. This report specifically focuses on innovation in the European retail industry. In it, we cover vendors offering AI software across three applications:
Accenture forecasts that growth in the AI healthcare market is expected to reach $6.6 billion by 2021 from $600 million in 2014, growing at an annual compound rate of 40%. We've covered AI in healthcare extensively on TechEmergence, but in this report we'll be looking at four European companies offering more niche solutions for both business and consumers in the healthcare space. We found that these solutions are intended to help CPG companies with at least one of the following business problems:
According to the International Health, Racquet & Sportsclub Association, the global fitness industry earned revenues estimated at $83.1 billion in 2016, up from $81 billion in 2015, and growing by 2.6%. If it continues at this rate, it should reach $87.5 billion in 2018. As of now, numerous AI vendors claim to assist gyms with signing up new gym customers, developing nutrition and fitness programs, and maintaining good customer relationships. Some offer chatbots that they claim can help gym members maintain personalized fitness regimens.
According to Deloitte, global healthcare spending is expected to grow annually by 4.1% from 2017-2021, up from just 1.3% in 2012-2016. The report suggests this growth will be fuelled by aging, rising populations, the growth of developing markets, advances in medical treatments, and rising labor costs.
Accenture forecast the Industrial Internet of Things could contribute $10 trillion to the global economy by 2030. The report also suggested that sensors, material tracking mechanisms, 3D printing, automated product design, robotics, and wearables could help manufacturers reduce costs and increase productivity. Predictive asset maintenance could potentially reduce equipment and machinery maintenance costs by up to 30% and result in up to 70% fewer breakdowns.
Episode Summary: In this episode of the AI in Industry podcast, we interview Rajat Mishra, VP of Customer Experience at Cisco, about the best practices for adopting AI in the enterprise and how business leaders should think about the man-machine balance at their companies.
Episode Summary: In this episode of the AI in Industry podcast, we interview Nikhil Malhotra, Creator and Head of Maker's Lab at Tech Mahindra, about how artificial intelligence changed the nature of IT services and business services in general. Malhotra talks about what businesses should consider to make themselves relevant for the future. In addition, he discusses the philosophy shift that has to happen for people to be appreciative of the process of problem-solving, and to see profit and growth from AI. We hope business leaders in the IT services industry will take from this interview the low-hanging fruit applications in the IT services industry.
Modern AI and machine learning software require large sets of data in order to train its algorithms to make judgments, make predictions, and take actions. Data is a critical part of bringing artificial intelligence to life in different industry sectors. The applications we’ve highlighted below involve organizing historical and real-time data from existing businesses in the retail sector from which data scientists can build machine learning models.
McKinsey reported that most oil and gas operators have not maximized the production potential of their assets. A typical offshore platform, according to the 2017 report, runs at about 77% of its maximum production potential. Industry-wide, the shortfall comes to about 10 million barrels per day, or $200 billion in annual revenue.
Episode Summary: Prominent technology companies like Google and Amazon lead the way in the B2C world, having access to streams of searches, clicks, and online purchases. They have access to large volumes of consumer data points numbering in the billions that can be used to train machine learning algorithms.
Allied Market Research estimated the value of the global autonomous vehicle (AV) industry to reach $54.23 billion in 2019, increasing to $556.67 billion by 2026 at an annual growth rate of 39.47% during that period. It follows that AI would find its way into the autonomous vehicle world. We detailed our own timeline for self-driving cars, pooling quotes and insights from executives at the top 11 global automakers.
Episode Summary: In this episode of the AI in Industry podcast, we interview Grant Ingersoll, CTO of Lucidworks, about AI developments in enterprise search, and the common challenges of AI adoption in enterprise.
A recent PricewaterhouseCoopers study revealed that the global market for drone-powered business solutions was valued at $127.3 billion in 2016. For agriculture, prospective drone applications in global projects were valued at $32.4 billion.
Forrester surveyed call center business leaders and found that 46% of them expect their business to grow by 5%-10% in 2019. To make this happen, Forrester reports that companies will increasingly explore the use of AI-driven chatbots and voice services.
International Data Corporation reports that the global wearables market continued to grow in the second quarter of 2018 as shipments reached 27.9 million units, an increase of 5.5% year-on-year. This growth translated to $4.8 billion year-on-year for the quarter. Smartwatches continued to be the most popular wearables.
Episode Summary: We receive a lot of interest from business leaders in the domain of data enrichment, and we've executed on a few campaigns for these businesses. At the same time, our audience seems particularly interested in the collection of data to train a bespoke machine learning algorithm for business, asking questions related to how to get started on data collection and from where that data could come.
Several factors have contributed to the advancement of AI in the pharmaceutical industry. These factors include the increase in the size of and the greater variety of types of biomedical datasets, as a result of the increased usage of electronic health records.