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ROBOTICS

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by EOS Intelligence EOS Intelligence No Comments

Can 3D Printing Move Beyond Design Customization in the F&B Industry?

First conceptualized over 40 years ago, 3D printing is still rapidly developing. The technology has been used in various industries ranging from 3D-printed human organs for implants to printing numerous customized products as per the customers’ requirement. There are several interesting applications of this technology in the Food & Beverage (F&B) industry as well. While currently they mostly pertain to creating visually complex geometrical food structures, there are also ongoing innovations with regard to using 3D printing for nutritional controllability and sustainability. However, most of these projects are one-off and 3D printing still remains a niche application in the F&B space.

3D printing is an evolving technology, offering F&B industry players benefits such as efficiency and customization. 3D printers are mostly used by F&B producers to make foods using the extrusion technique. In this method, the edible is in the form of a paste and is extruded from syringe-like containers onto a plate based on a 3D computer model. The process is similar to icing a cake using a piping bag, except with robotic precision, as the printer layers edible filament in desired shapes.

Traditionally, 3D food printing has been used to architect intricate shapes and designs that are difficult to achieve manually. It has been mostly confined to desserts such as chocolates and sweets as 3D printing offers huge potential for customization.

That being said, there is a gradual shift to adopt this technology in preparing more complex foods such as 3D-printed pizzas, spaghetti, burgers, and meat alternatives. For instance, since January 2022, BBB, an Israeli food chain has been serving 3D-printed burgers prepared from a mix of potato, chickpea, and pea protein. Similarly, since 2021, companies such as Spain-based Novameat and Israel-based Redefine Meat have been preparing 3D-printed beef steaks and other products using unique plant-based compounds that taste like blood, fat, and muscle that make up traditional meat flavors.

Printing beyond customization

While currently the main advantage of 3D printing in food is its ability to customize complex shapes and designs (thereby making it popular for creating chocolates, cakes, and cookies), it is also extending to customizing the level of nutrients in a meal. 3D printing offers the possibility to produce high-quality food concepts such as developing personalized meals by adding specific nutrients or flavors, ultimately giving more control over the food’s nutritional and flavor value.

With this idea in mind, a Netherland-based Digital Food Processing Initiative (DFPI) is testing this concept and trying to come up with a flexible food production system using 3D printing technology that will allow personalizing food at any time based on individual dietary choices. The collaboration is an ongoing project between the Dutch institution, Wageningen University & Research (WUR), global food and beverage companies GEA Group, General Mills, Tate & Lyle, and pharmaceutical company Solipharma B.V., together with Ministerie van Defensie, and a Netherland-based research organization, TNO, whose aim is to bring commercially viable personalized food products to the market, especially for military personnel and COPD (Chronic Obstructive Pulmonary Disease) patients.

Can 3D Printing Move Beyond Design Customization in the F&B Industry by EOS Intelligence

Another potential use of 3D printers is to reduce food wastage. The Netherland-based food-tech startup, Upprinting Food, which specializes in recycling organic food waste through 3D printing, has offered design services to various chefs and is also training restaurants to utilize their 3D printers to reduce food wastage. The company specializes in creating dishes out of any food left at restaurants and currently focuses only on high-end restaurants. They plan to expand their work towards retail and wholesalers in the future to reduce food wastage on a larger scale.

While 3D food printing seems to have a lot of unique uses, commercializing 3D-printed foods on a large scale has always been a challenge. For instance, printing a small piece (5x5x5 centimeter) of a food item takes around four to five minutes. Thinking about producing large-scale printed food would be difficult at this rate. In 2015, a project called the PERFORMANCE project (PERsonalized FOod using Rapid MAnufacturing for the Nutrition of elderly ConsumErs ) was shut down because it could not produce at a scale large enough to provide meals at nursing homes. The project focused on creating customizable meals for the elderly who had difficulties in chewing and swallowing. Thus, while customization of food products has immense use and strong growth potential in theory, it still needs a lot of work on improving speed and costs to facilitate its commercialization and feasibility.

Despite several advantages and functionalities, the market does not seem to use 3D printers for printing food as much as it could. It is mostly limited to confectionaries and very high-profile restaurants where quantities are small and prices are high. For instance, Natural Machines 3D printer, Foodini, is being used at Spain-based Michelin-star restaurant, La Enoteca, to prepare seafood, where food puree is printed into a flower-like shape, topped with caviar, sea urchins, hollandaise sauce, and carrot foam.

As per industry experts, 3D printing in F&B is still at an initial stage of development and will be more accepted once people see it being extensively adopted at restaurants. For now, 3D printing can be used to produce food with unique functionalities related to shape, taste, and texture such as printed pasta shapes of unique designs as offered by Italian food giant Barilla, through its spinoff business BluRhapsody as well as 3D-printed candy selfies by Magic Candy Factory, a spinoff of German candy manufacturer Katjes.

EOS Perspective

At present, 3D printing in food is largely limited to confectionaries. It is an evolving technology that offers considerable benefits of saving time and improving efficiency. It can potentially bring other advantages to the table, including reduction of food wastage, but such applications still require more research, investment, and trials, as well as attempts of expansion across food service formats, including small eateries and larger restaurants.

A 3D printing machine requires skill and appropriate training to print a meal. 3D food printing machines may not seem attractive for personal usage at this point but several food and beverage industry players have already moved in to adopt and exploit this innovative technology for various customized and attractive food options, although still largely at a pilot or experimental scale.

Most 3D food printers currently only cater to single restaurants or personal kitchens and are not very popular. For the technology to enter mainstream use and become attractive to broader audience, the printers need to be able print at large volumes. At the moment, there is a huge gap between what could be achieved with 3D printers in the F&B space and what has been actually tested and implemented. While several companies are working towards using this technology in innovative ways, there is a large space open for market disruption.

Google initiatives
by EOS Intelligence EOS Intelligence No Comments

Infographic: Google’s Tech Initiatives Transforming Industries

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Google, beyond being the leading search engine worldwide, is also one of the largest and most innovative companies. Through its innovations, Google along with other Alphabet companies (parent company of Google and its subsidiaries) is transforming various industries by empowering them with technology. Its solutions have reached diverse industries such as agriculture, manufacturing, healthcare, energy, and fishing, among others.

Innovation has always been at the core of Google’s strategy and it is bringing artificial intelligence (AI), machine learning, augmented reality, robotics, among others to shape various industries. It has introduced surgical robots to medicine, Google glass to manufacturing, AI-enabled programs to energy, among various other solutions that are revolutionizing these industries. We are taking a look at where Google has already left its innovative footprint.

Google’s Tech Initiatives Transforming Industries - EOS Intelligence

Alphabet companies included in the infographic:
Verily – Alphabet’s key research organization dedicated to the study of life sciences
Verb Surgical – A joint venture between Johnson & Johnson and Verily
DeepMind – Alphabet’s artificial intelligence company
Global Fishing Watch – An organization founded by Google in partnership with Oceana and SkyTruth
Surgical Robots – Marrying Cost-efficiency and Innovation
by EOS Intelligence EOS Intelligence No Comments

Surgical Robots – Marrying Cost-efficiency and Innovation

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Robotic-assisted surgeries, being minimally invasive, have been an excellent alternative for conventional open surgeries for quite some time now. Surgical robots use small incisions with broader 3D visualization of the operating area and precision-guided wrist movements. Players in the industry aim to develop solutions that combine medical device technology with robotic systems to provide patients with rapid post-surgery healing and reduced trauma. As surgeons perform an increasing number of procedures worldwide using these robots, the surgical robots market is growing along with the popularity of minimal-invasive surgeries.

Robotic-assisted surgeries have been rapidly adopted by hospitals in the USA, especially since 2000, when the Food and Drug Administration (FDA) approved the da Vinci Surgery System by Intuitive Surgical for general laparoscopic surgeries.

The system excelled its predecessors, such as PUMA 560 robotic surgical arm, which was used for non-laparoscopic surgeries in the late 1980s, by its 3D magnified high-resolution imaging and one centimeter diameter surgical arms to move freely inside the operating area.

These and other variants of surgical robots started to enter the market, enabling surgeons to operate complex minimally-invasive surgeries with improved precision, superior operative ergonomics, enhanced adroitness, and visualization compared to traditional laparoscopy.

Surgical Robots – Marrying Cost-efficiency and Innovation - EOS Intelligence

Robotics adoption focused on selected specialties

Even though robotic surgeries have been performed for quite some time, are still in the early stages of adoption in surgeries.

The adoption rate of robotic systems is uneven across various specialties with most robotic surgeries being performed in urology, gynecology, and general specialties. These fields also enjoy the fastest rate of adoption, example of which has been found in a 2017 study, in which researchers at Stanford University School of Medicine (California) analyzed data compiled by 416 hospitals on kidney removal procedures from 2013 to 2015. According to the study, robotic-assisted surgeries accounted for just 1.5% of all kidney removal surgeries in 2013, ration that increased to 27% by 2015.

Competition strengthens, challenges the market leader

In 2017, according to international market research and consulting firm, iData Research, surgical robotic systems market was valued over US$2.4 billion with over 693,000 robotic-assisted procedures performed in the USA alone. US-based Intuitive Surgical has long dominated the robotic surgery market with more than 4,800 da Vinci units installed around the globe, and approximately 877,000 surgical procedures performed with the da Vinci Surgical System in 2017. Intuitives’ da Vinci System is the only surgical robotic system which has been approved by FDA for various surgeries in gynecology, urology, cardiothoracic, thoracoscopic, and general surgeries.

In comparison, Intuitive’s competitor TransEntrix’s Sehnhance Robotic Surgical system received a nod from FDA in 2017 specifically for inguinal hernia and gall bladder removal laparoscopic surgeries, while also in the same year a robotic system for spinal surgeries, Mazor X by Mazor Robotics received FDA clearance.

Though Intuitive Surgical is the market leader, other players are not far from getting their products FDA-approved, a fact that has the potential to affect Intuitives’ leadership position.

Cost remains the main challenge for adoption

One major challenge for the robotic systems manufacturers is to convince hospitals to purchase their systems costing millions. For instance, a single da Vinci Surgical System costs around US$0.5 million to US$2.5 million, with additional disposable instruments whose costs range from US$700 to US$3,500 per procedure. Apart from the initial cost, there are other associated costs such as installation, service, and training fees that a hospital has to bear.

Players in this market started to realize that in order to strengthen their position and competitiveness, cost-effectiveness of their systems is the key requirement. Recently, several companies have increased their focus on developing cost-effective surgical robots, attempting not to compromise system’s performance.

Players in this market started to realize that in order to strengthen their position and competitiveness, cost-effectiveness of their systems is the key requirement

Examples of products competing on cost-effectiveness include Titan Medical’s SPORT surgical robotic system that is designed to perform various surgeries such as gynecology, urology, and general surgeries. At the outset, the system costs approximately US$0.95 million (da Vinci: ~US$1.8 million). Further the company claims the robotic system is cost-effective by driving down annual service and per procedure cost by increasing the number of times its disposable and reusable components can be used for various surgeries.

The market leader, Intuitive, also understands the costs pressures and has already established its presence with its low-cost robotic surgical system, da Vinci X, that costs approximately US$1.42 million, which is around US$780,000 cheaper as compared with Intuitive’s most advanced surgical robotic system da Vinci Xi which comes at a price of around US$2.2 million.

Other players are also entering the space, with Alphabet (Google) partnering with Ethicon (a subsidiary of Johnson and Johnson) to manufacture lower-cost surgical robot, planning to introduce it into the market by 2020.

Hospitals’ limited budgets trigger simpler products development

Considering that cost burden is the key challenge to robotics adoption even in large healthcare institutions, small hospitals are generally completely outside of the potential customer base, due to far lower budgets they have to work with.

At the same time, small hospitals feel the pressure to retain surgical patients, and in that they often want to turn to robot-assisted laparoscopic surgeries. As a result of this need paired with limited budgets, certain low-cost substitutes start to arrive to the market, at times indirectly challenging systems offered by the leading players in this area.

Examples of this include Olympus’ ENDOEYE FLEX 3D camera system and FlexDex, tools used for minimally invasive surgeries that allow for wristed-laparoscopy, giving robot-like dexterity without computers and no annual maintenance services.

According to a case presented at SAGES’ World Congress of Endoscopic Surgery in 2018 by Dr. Kent Bowden from Munson Cadillac Hospital, USA, contribution margin (portion of hospital revenue remaining after the variable cost to pay off hospital salaries, service contract, and other fixed costs) for a ventral hernia using da Vinci was US$ 8 per procedure while when using FlexDex it was US$2,605. For an inguinal hernia the contribution margin using da Vinci ranged from US$596 to US$698 whereas by using FlexDex, hospital contribution margin increased to US$1,601-US$1,115 per procedure.

Another example of such a substitute system is the FreeHand robotic arm produced by UK’s OR Productivity. FreeHand is a system that allows the surgeon to hold and control the laparoscope using his own head movements and a foot pedal. The system was developed to provide a range of benefits (stable image, reduced staff count, high precision) at an affordable installation and running cost. The producer promises a fixed per-procedure cost, whose rough estimation points to around US$197 per procedure (unachievable for procedures conducted with advanced systems).

It is clear that these simpler systems are not able to fully replace the higher-end products. However, these substitutes claim to be dexterous, cost-effective robotic solutions sufficient for certain procedures, thus can be perceived as an alternative (and competition) to expensive robots in some cases.

These substitutes claim to be dexterous, cost-effective robotic solutions sufficient for certain procedures, thus can be perceived as an alternative (and competition) to expensive robots in some cases

Robotic surgeries offer many advantages both for surgeons and patients, however, the equipment comes with certain challenges and limitations, which, apart from cost, include increased operating time in some cases, lack of tactile feeling for the surgeon, large space requirement, and long set-up time required for the robotic system. Having said that, cost-effectiveness is (and will continue to be) the main challenge players face while developing and marketing their systems.

EOS Perspective

Advancements in surgical robots are emerging by adding intelligence into the robotic systems with refined haptic feedback and versatility in robots’ arms. Companies are diving deep in this industry by improving their products and coming up with next-generation surgical robotic systems that could perform different types of minimally invasive surgeries.

Nevertheless, huge investment is needed for development of advanced and multi-skilled robots. Gaining investment for such projects is difficult, hence for the time being, it can be expected that the existing players are likely to consider forming partnerships to improve their products and increase their market share.

Gaining investment for such projects is difficult, hence for the time being, it can be expected that the existing players are likely to consider forming partnerships to improve their products and increase their market share

On the other hand, the market might see arrival of new systems based on existing technologies and solutions. They can be sourced from several of Intuitive’s patents that expired in 2016. These included some basic robotic concepts implemented in the robotic system, such as robotic arms control and imaging functionality. Several other patents developed by the company are expected to expire by 2022 (under the US patent law, a solution is protected for a relatively short period of time, generally 20 years).

Such availability of patent-free solutions will encourage other players in the industry to enter the market with similar products, probably at lower price points. This is likely to intensify the competition, which is already tightening, as Senhance robotic systems by TransEntrix got FDA received approval in 2018 for hernia repair and gallbladder removal, while SPORT by Titan Medical is expecting its approval in 2019, giving competition to da Vinci. Furthermore, a new partnership by Google and Johnson & Johnson is on the horizon, likely to bring some form of cost-effective alternative to the existing, more expensive systems, further adding pressure on the solutions offered by existing players.

Such availability of patent-free solutions will encourage other players in the industry to enter the market with similar products, probably at lower price points

The outlook for the robotic systems looks promising with mergers and partnerships among players that could drive innovation in this industry. Collaborating with hospitals to invest in training and application of robotic systems in growing number of procedures should also remain in the competitors’ focus area, as high number of robot-assisted procedures performed regularly provides opportunities for increasing the cost-efficiency and generating revenues that could be directed towards further R&D.

Players in the market need to focus on such high-volume procedures that will be likely to ultimately increase their sales, and allow them to focus on improving their products to deal with current challenges such as cost-effectiveness, limited portability and complex controls of the robotic systems, improving of which can help producers gain a competitive edge.

However, the players in this industry also need to identify new growth avenues – targeting areas where traditional laparoscopic surgeries are still predominantly performed but where robotic assistance could find its place, such as in colorectal and cholecystectomy procedures. There is still a considerable space in the market with opportunities. They can be tapped by putting emphasis on continuous investment in R&D aiming to innovate and develop new solutions that would find application in under-served therapeutic areas or offer new functionalities in order to cover as many therapeutic subsegments of the market as possible.

by EOS Intelligence EOS Intelligence No Comments

Slowly but Surely – Insurance Realizes AI’s Value

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Several sectors, such as banking, F&B, automotive, and healthcare have seen major transformations at the hands of artificial intelligence (AI) ‒ we discussed benefits of AI in fast food industry in our previous article – Artificial Intelligence Finds its Way into Your Favorite Fast Food Chain in November 2017. AI has become an integral part of a large number of industries, providing new solutions and facilitating greater back-end efficiency as well as customer engagement and management. Insurance sector, on the other hand, has been largely slow to react to this disruptive trend. In 2017, only about 1.3% of insurance companies invested in AI (as compared with 32% insurance companies that invested in software and information technologies). However, this is expected to change as insurance companies have begun to realize the untapped potential that AI unearths in all aspects of their business, i.e. policy pricing, customer purchase experience, application processing and underwriting, and claim settlement.

Insurance industry has been one of the sectors that have operated in their traditional form for several decades, without undergoing much of substantial transformation. This is also one of the reasons why the insurance sector has been relatively late in jumping on the AI bandwagon.

Artificial intelligence, which has significantly transformed the way several industries such as automotive, healthcare, and manufacturing operate, also presents a host of benefits to the insurance sector. Moreover, it is expected to drive savings not only for insurance companies but also brokers and policy holders.

Streamlining internal processes

AI has the ability to streamline several internal processes within insurance companies. There is a host of duplicating business operations in the insurance sector. Automation and digitization can result in about 40% cost cutting, and this can be achieved by automating about 30% of the operations.

This can be seen in the case of Fukoku Mutual Life Insurance. In 2017, this Tokyo-based insurance company replaced 34 employees with IBM’s Watson Explorer AI system that can calculate payouts to policyholders in faster and more precise manner. The company expects to boost productivity by 30% and is expected to save close to US$1.26 million (JPY 140 million) in the first year of operations. To put this in a perspective, the AI system cost the company, US$1.8 million (JPY 200 million), and its maintenance is expected to cost US$130,000 (JPY 15 million) per year. Therefore, Fukoku seems optimistic about achieving its return on investment within less than two years of installing the AI system.

In addition to providing automation of processes, AI can bring out disruptive transformation throughout the insurance value chain. Some of the most substantial benefits of using AI in the insurance sector are expected to be seen in policy pricing, offering of personalized insurance plans, as well as claim management.

Policy pricing

Traditionally, insurance companies used to price their policies by creating risk pools based on statistical sampling, thereby all insurance policies were based on proxy data.

AI is transforming this by moving policy pricing analysis from proxy data to real-time source data. Internet of Things (IoT) device sensors, such as telematics and wearable sensor data, enable insurance firms to price coverage based on real events and real-time data of the individuals that they are insuring.

An example of this is usage-based or pay-per-mile auto insurance, wherein a telematics sensor box (a black box for a car), is installed into a car to track information such as speed, driving distances, breaking habits, and other qualitative and quantitative driving data. Using this data, insurance companies can offer a customized policy to the car owner, charging lower premium from safe drivers or offering less-used cars the pay-per-mile option. It also helps insurance companies charge suitable premium from reckless drivers and long-distance drivers.

In February 2017, UK-based mobile network brand, O2, expanded into the auto insurance space with a telematics product called the O2 Drive. The device tracks different aspects of a user’s driving habits and offers discounts and personalized insurance policies based on it. The company is positioning its products to attract teen and young drivers as they are most likely to be open to sharing their driving data.

In addition to auto insurance, IoT devices such as wearable devices and smart home solutions also help in setting policy pricing in health and home insurance. US-based Beam Insurance Services uses a smart toothbrush to offer dental insurance. The company uses data accrued from the smart toothbrush, such as number of times a person brushes their teeth, duration of brushing, etc., to offer a personalized insurance policy. It claims to offer up to 25% lower rates in comparison with its competitors.

In another example, UK-based Neos Ventures offers IoT-powered home insurance based on a smart home monitoring and emergency assistance device. The device and its accompanying app helps users reduce instances of fire and water-based damages as well as break-ins and thefts. The premise of the company is that if they can successfully reduce the chances of any mishaps, they can offer cheaper premiums to the insured.

While IoT devices can greatly personalize insurance pricing, the largest caveat to the success of this pricing mechanism remains that customers must be willing to share their personal data with insurance providers to attain savings in the form of lower premium. As per Deloitte – EMEA Insurance Data Analytics Study 2017, about 40% of customers surveyed seemed open to track their behavior and share the data with insurers for more accurate premiums for health insurance, while 38% and 48% customers were open to tracking and sharing data in case of home and auto insurance, respectively.

Slowly but Surely – Insurance Realizes AI's Value

Customer purchase experience and underwriting of applications

The relationship between an insurance agent and the customer is an extremely important one for insurance companies. Many times the customer is dissatisfied with its interaction/experience with the insurance agent as they feel that the agent does not have their best interest at heart or the agent is not available for them as and when required.

This issue is effectively addressed with the use of AI-powered chatbots or virtual assistants. Advanced chatbots use image recognition and social data to personalize sales conversations and provide a better customer experience. Thus, agents and insurance representatives are being replaced by chatbots, which deliver faster and more efficient customer experience.

ZhongAn, a China-based pure online insurance company uses chatbots for 97% of its customer queries without any human involvement. It also uses AI to offer innovative insurance products, such as cracked mobile screen insurance. It uses image recognition technology to detect whether the image shows the mobile screen is cracked or intact. It can also decipher if the picture has been photoshopped or altered to ensure the claim is genuine. Since its inception in 2013, the company has sold about 8 billion policies to 500 million customers (these include cracked mobile insurance as well as the company’s other popular products).

To blend the human experience with chatbots, companies have started branding their chatbots with human names. New York-based P2P insurance company, Lemonade, uses exclusively chatbots named Maya and Jim to interact with customers and create personalized insurance options in less than a minute within the Lemonade app. The chatbots Maya and Jim are alter-egos of the company’s real-life employees with the same names.

Similarly, in December 2016, ICICI Lombard General Insurance launched a chatbot called MyRA. Within six months of operations the virtual assistance platform sold 750 policies without any human intervention, while it was used by 60,000 consumers for queries.

In addition to elevating customer’s purchase experience, AI also helps in reducing insurance underwriting/processing time and ensuring higher quality. The underwriting process traditionally has a range of manual tasks that make the process slow and also prone to human errors. However, AI helps achieve quicker and more reliable data analysis. AI tools such as Machine Learning and Natural Language Processing (NLP) help underwriters scan a customer’s social profile to gather important data, trends, and behavioral patterns that can result in more accurate assessment of the application.

New-York based Haven Life (a subsidiary of MassMutual), leverages AI technology to underwrite its life insurance policies. It requires its customers to submit a 30-question application (which is more conversational in nature as compared with the detailed traditional life insurance forms) and upload few documents such as medical records, motor vehicle driving records, etc. The AI technology analyzes the provided information along with historical life insurance data and asks additional questions if required. In several cases, it also offers coverage without the mandated medical test. Through AI, the company has reduced its underwriting time from the typical 1-2 weeks to as low as 20 minutes.

Claim management

AI can play a significant role in two of the most critical aspects of claim management, i.e. the time to settle a claim and fraud detection.

The time to settle a claim is one of the performance metrics that customers care most about. Using AI, companies can expedite the claim process. Chatbots are used to address the First Notice of Loss (FNOL), wherein customers submit their claims by sending pictures of the damaged goods along with answering few questions. The chatbot then processes the claim and assesses the extent of loss and its authenticity, to determine the correct amount for claim settlement.

Lemonade set a world record in December 2016 by settling a claim using its AI bot, Jim, in only three seconds. The AI bot reviewed the claim, cross-referenced it against the policy, ran several anti-fraud algorithms, approved the claim, sent wiring instructions to the bank, and informed the customer in the three-second window.

Another interesting area of application is in agriculture, where machine learning can also help quickly analyze claims (pertaining to loss spread over a wide area) using satellite imaging, which would otherwise take humans significantly greater time and costs to ascertain.

As mentioned earlier, AI can bring massive savings to insurance firms by reducing fraudulent claims. As per US-based Coalition Against Insurance Fraud (CAIF) estimates, insurance carriers lose about US$80 billion annually in fraudulent claims. AI technologies provide insurance firms with real-time data to identify duplicate and inflated claims as well as fake diagnoses.

In addition, many companies use AI to run algorithms on historical data to identify sequences and patterns of fraudulent claims to identify traits and trends that may be missed by the human eye during the initial stages of claim processing.

According to CAIF, in November 2016, about 75% of insurance firms used automated fraud detection systems to detect false claims. Paris-based Shift Technologies is one of the leading players in this domain, claiming to have a 250% better fraud identification rate as compared with the market average. The company had analyzed more than 100 million claims from its inception in 2013 up till October 2017.

EOS Perspective

There is no denying that AI has the capability to transform the insurance industry (as it has transformed many other industries). Although, initially slow at reacting to the AI trend, insurance companies have realized its potential.

As per an April 2017 Accenture survey, about 79% of the insurance executives believed that AI will revolutionize the way insurers gain information from and interact with their customers. This is also visible in the recent level of investments made in AI by the insurance sector. TCS’s Global Trend Study on AI 2017 stated that the insurance sector outspent all the other 12 sectors surveyed (including travel, consumer packaged goods, hospitality, media, etc.) by investing an average of US$124 million annually in AI systems. The cross industry average of the 13 sectors stood at US$70 million.

Thus, it is very important for insurance players to get on board the AI trend now. Since they are already late (in comparison to some other industries) in reacting to the trend, it is critical that they adapt to it to remain relevant and competitive.

However, the key barrier to AI implementation are the complex and outdated legacy systems that hold back innovation and digitization. The companies that do not manage to implement tech innovations in their legacy systems due to high cost might just be acting penny wise, pound foolish.

by EOS Intelligence EOS Intelligence No Comments

Is Technology the Solution to the Next Food Crisis?

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The UN estimates rapid population growth with additional 2-3 billion people globally by 2050. To feed this swelling population, food production needs to scale up by 70%, otherwise we are likely to be at risk of a global food crisis. With resources becoming scarce and climate change diminishing crop production by 2% per decade, food production methods need radical transformation and technology could be the possible solution to it. Using technology in farms and fields holds extraordinary promise of helping the agriculture sector become more efficient, productive, and sustainable.

Population increase, resource limitations, and climate change are putting pressure on farmers to produce more with less. To boost production it is essential to efficiently manage farm inputs such as seeds, fertilizers, and pesticides, optimize sowing and harvesting cycles, monitor field data (soil condition, plant stress, etc.) for improved crop yield, among others. However, managing these inputs is cumbersome and laborious without consistent and precise monitoring. Unfortunately, many farmers still rely on guess work and traditional processes instead of actual data to make all farming decisions. Technology could prove useful by helping farmers to closely monitor all farm activities and take informed data-driven decisions to improve production levels.

Technology can offer relief to pressures in agriculture

Emerging technologies such as weather tracking, robotics, and Internet of Things (IoT) can consistently monitor every aspect of agriculture such as soil fertility, health of farm animals, temperature and humidity conditions, optimal time to sow and harvest, schedule chemical application on fields, analyze irrigation requirements, among several other functions.

Weather forecast-based predictive modelling

Weather is a crucial determinant to ascertain the best time to sow, fertilize, spray, irrigate, and harvest crops. About 90% of crops losses are due to weather events and 25% of those losses could be avoided by using weather forecast-based predictive modelling on farms. Integrating weather forecast models with farming practices could enable better decision-making and improve crop yield. Companies such as John Deere, Ignitia, etc., already offer comprehensive weather-based farming solutions.

Robotics

Robotics is another emerging technology gaining traction in the agriculture sector. With robots capable of executing all functions from sowing to harvesting, they could easily replace human labor in the foreseeable future, particularly, at a time when some countries are facing labor shortage. For instance, in 2017, the UK suffered from 20% shortfall in migrant labors, which was mostly blamed on the Brexit vote that has made the UK unattractive for overseas workers to seek employment. The labor shortage is likely to get worse in 2018, making harvesting at labor-intensive vegetable and fruit fields difficult. Hence, some farms across the UK are considering to employ farm robots for vegetable and fruit picking.

Robots are also far more efficient than human labor, which is the key requirement to boost food production – each Harvest CROO Robotics’ robot (made by a US-based company that develops robots for the agriculture sector) is capable of harvesting eight acres in a day, which is equivalent to the work of 30 human pickers.

Internet of Things

Further, IoT has gained significance across several industries and has now entered the farms. IoT is turning farms into a mesh of smart sensors connected in a network, with the help of which every granular detail of crop, soil, livestock, or farm can be analyzed, thus, enabling farmers to devise smart cropping techniques and farming methods. IoT can streamline farming processes, reduce water consumption, and improve production and bottom lines.

EOS Perspective

Eventually, the growing population will put pressure on food supply. In such a scenario, digital farming is the best possible solution to escape the looming food crisis. Technology promises improved communication systems, precise monitoring devices, recommendations that could improve all processes between sowing and harvesting, and efficient livestock monitoring, among others, that could boost agricultural yields, reduce food wastage, decrease the inputs or resources needed per unit of output, and ensure sustainable farming practices.

However, most farmers have not adopted digital farming solutions and the use of technology is far from being a mass phenomenon yet. Cost is the most significant barrier to adoption, with most farms unable to bear the high upfront costs. Another common challenge is the lack of robust communication and internet network in rural areas as well as the absence of awareness and skills among farmers to apply technologies in farms.

Most farmers have not adopted digital farming solutions and the use of technology is far from being a mass phenomenon yet. Cost is the most significant barrier to adoption.

Consequently, the development of digital farming will require commitment and intervention by governments across the world, to offer incentives and cover the substantial start-up costs. Fortunately, few organizations have already started undertaking initiatives to tackle challenges. For instance, Mimosa Technology (a Vietnam-based IoT solution provider for agriculture sector) leases IoT-based hardware devices to farmers’ cooperatives in Vietnam to lessen the cost burden for smallholder farmers.

Initiatives are also being taken to ensure network connectivity and improve digital literacy in remote/rural areas – for example, governments of Thailand, India, or the UK, to name a few, are planning to boost digital connectivity in rural areas.

Eventually, technological innovations can be expected to make farming practices precise and to improve output. The use of digital farming solutions is an answer to the probable food crisis but for it to succeed, a mass adoption of technology across farms is a necessity. With growing awareness of benefits of automation in fields and efforts made by various organizations and governments to overcome challenges, digital farming would sooner than later transform the agriculture sector.

Brief description of companies and projects:

  • CropX: A USA-based agriculture-analytics company
  • CLAAS: A Germany-based agricultural machinery manufacturer
  • SmaXtec: An Austria-based provider of solutions to monitor livestock
  • Farmers Edge: A Canada-based company offering digital solutions for agriculture
  • The Weather Company: A USA-based weather forecasting and information technology company, a part of IBM
  • John Deere: A USA-based manufacturer of machinery for agriculture, construction, and forestry
  • Ignitia: A Sweden-based weather forecasting company
  • Robot Thorvald (to be launched): A robot developed by Saga Robotics, a Norway-based manufacturer of robots
  • Deepfield robotics: Robots developed by Bosch, a Germany-based engineering and electronics company
  • Hands Free Hectare: A project developed by Harper Adams University and Precision Decisions
  • Robot Agbot: A robot designed and built by QUT (an Australian university) with support from the Queensland Government
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Infographic: Four Digital Trends in Aviation that Will Fly High in 2018

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Emerging technologies are sprawling over the aviation sector making travel seamless, convenient, automated, and personalized. Airports and airlines are adopting technologies that simplify the passengers’ travel experience by digitalizing baggage and boarding processes, making wayfinding in busy airports efficient, and making check-ins more rapid, among many others. Digitalization is not only helping to deliver greater customer satisfaction, but also minimizing costs, increasing revenue, and improving efficiency – for instance, within six months of chatbot usage, Aeromexcio was able to reduce average customer service resolution time via chat to two minutes from 16 minutes.

Some of the key technologies to flourish in aviation in 2018 include biometrics, artificial intelligence-powered chatbots, robotics, and Internet of Things. With emerging technologies set to redefine the travel experience, it is essential that the airports and airlines take action now to ascertain they are well-placed to tap the opportunity.

digital trends in aviation

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Note: Mexico-based airline:Volaris; Germany-based airline:Lufthansa; Netherlands-based airline:KLM; UK-based airline:Virgin Atlantic; USA-based airlines:Delta, JetBlue; Taiwan-based airline:EVA Air; New Zealand-based airline:Air New Zealand

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Artificial Intelligence Finds its Way into Your Favorite Fast Food Chain

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The idea of robots replacing humans has always seemed like talks of the future, however, it is not as distant as it seems, especially when it comes to the fast food industry. The fast food market, which is characterized by cut-throat competition and high share of low-skilled jobs, has recently been swept by a technology wave. Leading players, such as Domino’s, Starbucks, or KFC, are investing heavily in artificial intelligence (AI) to increase efficiencies and differentiate themselves in this overly crowded industry – some are integrating it with their back-end operations while others with the consumer interface. However, with investments in technology increasingly becoming an industry trend, the question remains if AI will provide the competitive edge to these players or are consumers yet not quite ready to lose the human touch.

Artificial intelligence has been the buzz word for some time and the fast food industry is also catching on the wave. With some market leaders claiming to be as much a technology company (owing to huge technology budgets) as a food business, these players are incorporating AI in several verticals to improve operational efficiencies and elevate consumer experience.

The wave of AI adoption is particularly prominent in the US market, where labor costs are increasing significantly, hence AI is being seen as a tool to reduce costs in the long run. Just recently, in the beginning of 2017, minimum wages have been increased in 19 states and will reach US$13.50/hour in Washington state and even US$15/hour in California by 2022 (the minimum wages in 2017 stood at US$11 and US$10.50 for Washington state and California, respectively).

Apart from the need to control costs, the interest in AI is driven by the fact that it provides food business with great advantage – the use of AI helps companies gather valuable data about customer choices, flavor trends, etc., and use this information effectively.

Leading players, such as Domino’s, Starbucks, KFC, and CaliBurger, have already started using AI is different verticals of their businesses to not only reduce costs but also to remain one step ahead of the changing consumer expectations.

Domino’s

Domino’s can be easily slated as one of the most aggressive fast food players when it comes to adoption of technology. The company has embraced AI in several aspects of its operations aiming to smoothen both the ordering and the delivery sides of the business.

In early 2017, Domino’s launched an AI-based technology called the DRU (Domino’s Robotics Unit) Assist, which enables consumers to order a pizza on the app using their voice. The in-app AI assist, which was built in partnership with natural language company, Nuance, converses with customers in a human-like manner and discusses orders, menus, ingredients, store locations, and operating hours.

Along similar lines, the company has also launched its Facebook messenger bot, wherein customers can converse with the bot on the messenger app to learn about menu options, discount offers, and also order food. In addition, Domino’s is in the process of launching its ‘Domino’s Anywhere’ feature, through which customers can drop an exact location pin using GPS (as in case of Uber) when ordering pizza thereby facilitating delivery at various locations, such as parks, and other public places without providing an exact address.

Simultaneously, the company is also using AI to automate the delivery process. In November 2016, in New Zealand, Domino’s partnered with Flirtey, a drone company, to undertake the first commercial delivery of food by a flying drone. While this technology is largely futuristic for mass adaptation, the company is focusing on land-based autonomous delivery vehicles to deliver pizza to customers’ doorsteps. This technology went to trial in June 2016 in Australia and in 2017 in Germany, while the company plans to roll it out in the Netherlands for customers within the one-mile radius by the end of 2017. The technology, which is provided by Starship Technologies (a European start-up), has GPS tracking, computer vision and object detection capabilities, and can travel within a three mile radius, carrying up to 10kg weight for a cost as low as US$1.32 (£1).

McDonald’s

McDonald’s is one of the recent players to blend fast food with technology. The company stated that its investments in technology are to be one of its key strategies in 2017, calling it the ‘Experience of the Future’ strategy. As per its plans, McDonald’s aims to replace cashiers with self-ordering kiosks in 2,500 of its restaurants by the end of 2017 and in another 3,000 restaurants by the end of 2018. The cost of each kiosk is estimated at about US$50,000-60,000.

In addition to this, the company plans to roll out mobile ordering across 14,000 US locations by the end of 2017. Mobile ordering will not only ease the ordering process but also help the company gain access to valuable customer data, which in turn can be used to recommend additional dishes and personalized deals. McDonald’s has already launched mobile ordering in Japan and received a positive response with customers using the app ordering about 35% more than usual.

Since 2015, the company has also been rolling out digital menu displays across its stores in the USA as well as globally. They use AI to highlight weather-appropriate options. This feature has resulted in increased sales by 3-3.5% in Canada.

Starbucks

Starbucks has also developed an artificial intelligence program to improve customer ordering experience. The program, which is known as the Digital Flywheel program, links itself with the accounts of Starbuck Reward members and makes order suggestions based on order history, weather conditions, time of day, weekend/workday, and other such factors. In addition, it brings additional convenience to the ordering process for the Reward program members, who can order directly from push notifications or text message and collect their ready order from a nearby Starbucks.

Moreover, embracing the voice computing trend, the company has launched an AI-based ordering system on its app that allows customers to order and pay for their orders using voice. The company has also launched a ‘Starbucks Reorder Skill’ for users of the Amazon Alexa app, wherein users who have linked their Starbucks account to their Amazon Alexa account can re-order their usual drink (at one of the last 10 visited Starbucks stores) by simply saying “Alexa, order my Starbucks”. However, this service is currently limited to the order of the users’ usual designated drink instead of ordering anything off the menu.

Starbucks has made significant investments in technology on a continuous basis, having invested close to US$275-300 million in its partners and digital initiatives globally in 2016, an increase from an investment of US$145 million in 2015.

KFC

While most quick service restaurants players are using technology to elevate their app-based ordering experience, KFC in China is taking a different route to join the AI bandwagon. In April 2016, KFC (in collaboration with Baidu, China’s leading search engine) launched a robot-run restaurant in Shanghai called Original+. The restaurant is run by a robot named Dumi, which takes customer orders and is smart enough to handle order changes and substitutes. While the robot can understand the three main dialects of Mandarin spoken in China, it cannot distinguish other dialects and accents. The payment at the outlet is made through smartphones via mobile payment systems.

The collaboration opened another AI-enhanced café in Beijing in December 2016, wherein customers take pictures of themselves with a machine, which then recognizes the users face, sex, age, and mood, along with analyzing the time of the day to recommend suitable meal options and completes the ordering process. Moreover, upon revisit, the machine recognizes the user and shows order history as well as dining preferences to quicken the order process. However, unlike the Shanghai restaurant, this restaurant also offers the traditional ordering process. While these may seem futuristic, the company has expressed its plans to open more smart restaurants in the country.

CaliBurger

Apart from market leaders, smaller players, such as CaliBurger, are also investing heavily in technology in both the front and back end of their operations. The California-based burger chain has brought AI into their kitchens through the use of AI-enabled robot, called Flippy, which is capable of cooking/flipping burgers and placing them on the bun. The robot, which was launched in March 2017 in the chain’s Pasadena, California outlet is created by Miso Robotics, a pioneer in the robotics for restaurant business. The concept is currently in test run and if successful, it is expected to be rolled out in early 2018 with expansion plans to more than 50 outlets worldwide by 2019.

EOS Perspective

It remains no secret that most leading and few niche smaller players are turning to AI to elevate their service levels in this competitive industry. Companies which have traditionally not taken the digital route up till now are also joining the technology bandwagon. Pizza Hut, which has always been one step behind Domino’s with regards to technology deployment, has invested US$12 million in technology in Q2 2017 towards improving its digital and delivery services. The chain plans to invest US$180 million in a technology overhaul by the end of 2018.

It can be expected that at this stage of technology development most of the automation will be successfully implemented in the customer-facing side of the business, and will comprise technologies such as bots and voice recognition that can be integrated into apps and other ordering mediums. This not only helps consumers by easing the ordering process but also helps companies gather valuable data about customer preferences and ordering trends, which in turn can be used for providing complementing recommendations and thereby increasing sales. While AI-enhanced ordering and payment may be the path of the future, it will be far-fetched to say that it will eliminate the need for humans in this side of the industry altogether. With increased sales due to AI-based ordering, the need for humans will remain, however, their role may evolve from ordering to management.

The adoption of AI or automation at the food preparation and delivery end, on the other hand, still seems a little futuristic. While several players, such as Domino’s and CaliBurger, have started investing and launching this technology, the wide application of it seems distant. This is especially true in the food preparation tasks, due to an increasing trend towards customization of orders and the growing use of complex ingredients to cater to niche audiences that require dairy-free, vegan, gluten-free, or other such options. Till the time robots that can handle such complexities are developed, these jobs will largely be conducted by humans with maybe automating the easier aspects of the process (such as flipping the burgers). Moreover, with the fast changing consumers’ needs it will be hard for robotics companies to preempt the trends and develop robots that can match the required skill sets both now and in the future.

That being said, the use of AI by the restaurant industry is definitely on the rise and while we may not know the extent to which it will take over the current operations, we can definitely be sure that this is increasingly becoming the point of focus as well as innovation in this highly competitive space.

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