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Automotive Industry Gearing towards Digital Transformation with AI

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Artificial intelligence (AI) has become an integral part of almost every industry, and the automotive sector is no exception. From self-driving cars to predictive maintenance, AI is evolving as a major disruptor in the auto industry, slowly transforming how automobiles are designed, manufactured, and sold. This digital swing is driven mainly by increased competition, consumer preferences for smart mobility, and the benefits of AI. However, AI adoption in the automotive industry is not mainstream yet, with the technology deployed only at the pilot level and in selective business segments. As the world gears toward an era of digital transformation and automation, AI is expected to be part of various business processes in the automotive industry in the coming years.

Artificial intelligence in the auto industry is typically associated with autonomous and self-driving cars. However, the technology has increasingly found its way into other applications over the last few years. Leading auto OEMs are showing an interest in deploying AI-driven innovations across the value chain, investing in tech start-ups, partnering with software providers, and building new business entities.

For instance, a venture capital fund owned by Japanese automaker Toyota, Toyota AI Ventures (rebranded as Toyota Ventures now), with US$200 million in assets under management, invested in almost 35 early-age startups that focus on AI, autonomy, mobility, and robotics between 2017 and 2020. Similarly, in 2022, South Korean automotive manufacturer Hyundai invested US$424 million to build an AI research center in the USA to advance research in AI and robotics. In the same year, CARIAD, a software division of the Germany-based Volkswagen Group, acquired Paragon Semvox GmbH, a Germany-based company that develops AI-based voice control and smart assistance systems, for US$42 million.

Changing consumer preferences, competitive pressures, and various advantages of AI are driving this transformation. According to a 2019 Capgemini research study, nearly 25% of auto manufacturers in the USA implemented AI solutions at scale, followed by the UK (14%) and Germany (12%) by the end of 2019.

There are numerous applications of AI in the automotive industry. Some of the more common and innovative uses of AI include virtual simulation models, inventory management, quality control of parts and finished goods, automated driver assistance systems (ADAS), predictive maintenance, and personalized vehicles, to name a few.

Automotive Industry Gearing towards Digital Transformation with AI by EOS Intelligence

AI-based virtual simulation models used for effective R&D processes

Due to changing customer preferences, increasing regulations concerning safety and fuel emissions, and technological disruption, OEMs are finding it more expensive to make cars nowadays. A 2020 report by PricewaterhouseCoopers says that conceptualization and product development account for 77% of the cost and 65% of the time spent in a typical automotive manufacturing process.

To make R&D cost-effective and more efficient, some auto manufacturers and tier-I suppliers are turning to AI. AI enables the simulation of digital prototypes, eliminating a lot of physical prototypes, thus reducing the costs and time for product development. One interesting concept that is emerging and catching attention in this area is the “digital twin”. The concept employs a virtual model mimicking an entire process or environment and its physical behavior. There are numerous uses of digital twins – in vehicle design and development, factory and supply chain simulations, autonomous driving simulations, etc. In vehicle design and development, digital twins make simulations easier, validate each step of the development in order to predict outcomes, improve performance, and identify possible failures before the product enters the production line.

For instance, in 2019, Continental, a Germany-based automotive parts manufacturing company, entered into a collaboration with a Germany-based start-up, Automotive Artificial Intelligence (AAI), to develop a modular virtual simulation program for its Automated Driver Assistance System (ADAS) application and also invested an undisclosed amount in the company. The virtual simulation program could generate phenomenal vehicle test data of 5,000 miles per hour compared to 6,500 miles of physical test driving per month, reducing both time and costs.

Many leading automotive companies are also looking to utilize this innovative concept in streamlining the entire manufacturing operations. For example, in early 2023, Mercedes-Benz announced that the company is partnering with Nvidia Technologies, a US-based technology company specializing in AI-based hardware and software, to build a digital twin of one of its automotive plants in Germany. Mercedes-Benz is hoping that the digital twin can help them monitor the entire plant and make quick changes in their production processes without interruptions.

General Motors, Volkswagen, and Hyundai use AI for smart manufacturing

Automation processes and industrial robots have been in automotive manufacturing for a long time. However, these systems can perform only programmed routine and repetitive tasks and cannot act on complex real-life scenarios.

The use of AI in automotive manufacturing makes these production processes smarter and more efficient. Some of the applications of AI in manufacturing include forecasting component failures, predicting demand for components and managing inventory, using collaborative robots for heavy material handling, etc.

For instance, General Motors, a US-based automotive manufacturing company, has been using AI-based design strategies since 2018 to manufacture lightweight vehicles. In 2019, the company also deployed an AI-based image classification tool in its robots to detect equipment failures on pilot-level experimentation.

Similarly, a Germany-based luxury car manufacturer, Audi, has been using AI to monitor the quality of spot welds since 2021 and is also planning to use AI in its wheel design process starting in 2023. In 2021, Audi’s parent company, Volkswagen, also invested about US$1 billion to bring technologies such as cloud-based industrial software, intelligent robotics, and AI into its factory operations. With this, the company aims to drive a 30% increase in manufacturing performance in its plants in the USA and Mexico by 2025.

In another instance, South Korean automotive manufacturer Hyundai uses AI to improve the well-being of its employees. In 2018, the company developed wearable robots for its workers, who spend most of their time in assembly lines. These robots can sense the type of work of employees, adjust their motions, and boost load support and mobility, preventing work-related musculoskeletal disorders. Thus, AI is transforming every facet of automobile manufacturing, from designing to improving the well-being of employees.

Companies provide more ADAS features amidst increasing competition

Automated Driver Assistance System (ADAS) is one of the powerful applications of AI in the automotive industry. ADAS are intelligent systems that aim to make driving safer and more efficient. ADAS primarily uses cameras and Lidar (Light Detection and Ranging) sensors to generate a high-resolution 360-degree view of the car and assists the driver or enables cars to take autonomous actions. Demand for ADAS is growing globally due to consumers’ rising preference for luxury, better safety, and comfort. It is estimated that by 2025, ADAS will become a default feature of nearly every new vehicle sold worldwide. ADAS is classified into 6 levels:

Level 0 No automation
Level 1 Driver assistance: the vehicle has at least a single automation system
Level 2 Partial driving automation: the vehicle has more than one automated system; the driver has to be on alert at all times
Level 3 Conditional driving automation: the vehicle has multiple driver assistance functions that control most driving tasks; the driver has to be present to take over if anything goes wrong
Level 4 High driving automation: the vehicle can make decisions itself in most circumstances; the driver has the option to manually control the car
Level 5 Full driving automation: the vehicle can do everything on its own without the presence of a driver

At present, cars from level 0 to level 2 are on the market. To meet the growing competitive edge, several auto manufacturers are adding more automation features to the level 2 type. Companies have also been making significant strides toward developing autonomous vehicles. For instance, auto manufacturers such as Mercedes, BMW, and Hyundai are testing level 3 autonomous vehicles, and Toyota and Honda are testing and trialing level 4 vehicles. This indicates that the future of mobility will be highly automated relying upon technologies such as AI.

Volkswagen and Porsche use AI in automotive marketing and sales

There are various applications of AI in marketing and sales operations – in sales forecasting and planning, personalized marketing, AI-assisted virtual assistants, etc. According to a May 2022 Boston Consulting Group (BCG) report, auto OEMs can gain faster returns with lower investments by deploying AI in their marketing and sales operations.

Some automotive companies have already started to deploy AI in sales and marketing. For instance, since 2019, Volkswagen has been leveraging AI to create precise market forecasts based on certain variables and uses the data for its sales planning. Similarly, in 2021, a Germany-based luxury car manufacturer, Porsche, launched an AI tool that suggests various vehicle options and their prices based on the customer’s preferences.

Automakers integrate AI-assisted voice assistants into cars

Cars nowadays are not only perceived as a means of transportation, but consumers also expect sophisticated features, convenience, comfort, and an enriching experience during their journey. AI enhances every aspect of the cockpit and deploys personalized infotainment systems that learn from user preferences and habits over time. Many automakers are integrating AI-based voice assistants to help drivers navigate through traffic, change the temperature, make calls, play their favorite music, and more.

For instance, in 2018, Mercedes-Benz introduced the Mercedes Benz User Experience (MBUX) voice-assisted infotainment system, which gets activated with the keyword “Hey Mercedes”. Amazon, Apple, and Google are also planning to get carmakers to integrate their technologies into in-car infotainment systems. It is expected that 90% of new vehicles sold globally will have voice assistants by 2028.

Integration and technological challenges hamper the adoption of AI

The adoption of AI in the automotive industry is still at a nascent stage. Several OEM manufacturers in the automotive industry are leveraging various AI solutions only at the pilot level, and scaling up is slow due to the various challenges associated with AI.

At the technology level, the creation of AI algorithms remains the main challenge, requiring extensive training of neural networks that rely on large data sets. Organizations lack the skills and expertise in AI-related tools to successfully build and test AI models, which is time-consuming and expensive. AI technology also uses a variety of high-priced advanced sensors and microprocessors, thus hindering the technology from being economically feasible.

Moreover, AI acts more or less like a black box, and it remains difficult to determine how AI models make decisions. This obscurity remains a big problem, especially for autonomous vehicles.

At the organizational level, integration challenges make it difficult to implement the technology with existing infrastructure, tools, and systems. Lack of knowledge of selecting and investing in the right AI application and lack of information on potential economic returns are other biggest organizational hurdles.

EOS Perspective

The applications of AI in the automotive industry are broad, and many are yet to be envisioned. There has been an upswing in the number of automotive AI patents since 2015, with an average of 3,700 patents granted every year. It is evident that many disrupting high-value automotive applications of AI are likely to be deployed in the coming decade. Automotive organizations are bolstering their AI skills and capabilities by investing in AI-led start-ups. These companies together already invested about US$11.2 billion in these startups from 2014 to 2019.

There is also an increase in the hiring pattern of AI-related roles in the industry. Many automotive industry leaders are optimistic that AI technology can bring significant economic and operational benefits to their businesses. AI can turn out to be a powerful steering wheel to drive growth in the industry. The future of many industries will be digital, and so will be for the automotive sector. Hence, for automotive businesses that are yet to make strides toward this digital transformation, it is better to get into this trend before it gets too late to keep up with the competition.

by EOS Intelligence EOS Intelligence No Comments

Agritech in Africa: How Blockchain Can Help Revolutionize Agriculture

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In the first part of our series on agritech in Africa, we took a look into how IT and other technology investments are helping small farmers in Africa. In the second part, we are exploring the impact that potential application of advanced technologies such as blockchain can have on the African agriculture sector.

Blockchain, or distributed ledger technology, is already finding utility across several business sectors including financial, banking, retail, automotive, and aviation industries (click here to read our previous Perspectives on blockchain technology). The technology is finding its way in agriculture too, and has the potential to revolutionize the way farming is done.


This article is the second part of a two-piece coverage focusing on technological advancements in agriculture across the African continent.

Read part one here: Agritech in Africa: Cultivating Opportunities for ICT in Agriculture


State of blockchain implementation in agriculture in Africa

Agricultural sector in Africa has already witnessed the onset of blockchain based solutions being introduced in the market. Existing tech players and emerging start-ups have developed blockchain solutions, such as eMarketplaces, agricultural credit/financing platforms, and crop insurance services. Companies, globally as well as within Africa, are harnessing applications of blockchain to develop innovative solutions targeted at key stakeholders across the food value chain.

Blockchain to promote transparency across agriculture sector

The most common application of blockchain in any industry sector (and not only agriculture) is creating an immutable record of transactions or events, which is particularly helpful in creating a trusted record of land ownership for farmers, who are traditionally dependent on senior village officials to prove their ownership of land.

Since 2017, a Kenyan start-up, Land LayBy has been using an Ethereum-based shared ledger to keep records of land transactions. This offers farmers a trusted and transparent medium to establish land ownership, which can then further be used to obtain credit from banks or alternative financing companies. BanQu and BitLand are other examples of blockchain being used as a proof of land ownership.

This feature of blockchain also enables creation of a transparent environment where companies can trace the production and journey of agricultural products across their supply chain. Transparency across the supply chain helps create trust between farmers and buyers, and the improved visibility of prices further down the value chain also enables farmers to get better value for their produce.

In 2017, US-based Bext360 started a pilot project with US-based Coda Coffee and its Uganda-based coffee export partner, ​​Great​ ​Lakes​ ​Coffee. The company developed a machine to grade and weigh coffee beans deposited to Great Lakes by individual farmers in East Uganda. The device uploads the data on a blockchain-based SaaS solution, which enables users to trace the coffee from its origin to end consumer. The blockchain solution is also used to make payments to the farmers based on the grade of their produce in form of tokens.

In 2017, Amsterdam-based Moyee Coffee also partnered with KrypC, a global blockchain, to create a fully blockchain-traceable coffee. The coffee beans are sourced from individual farmers in Ethiopia, and then roasted within the country, before being exported to the Netherlands.

This transparency can help food companies to isolate the cause of any disease outbreak impacting the food value chain. This also allows consumers can be aware of the source of the ingredients used in their food products.

Agritech in Africa: How Blockchain Can Help Revolutionize Agriculture by EOS Intelligence

Blockchain-based platforms to improve farmer and buyer collaboration

Blockchain can also act as a platform to connect farmers with vendors, food processing, and packaging companies, providing a secure and trusted environment to both buyers and suppliers to transact without the need of a middleman. This also results in elimination of margins that need to be paid to these intermediaries, and helps improve the margins for buyers.

Farmshine, a Kenyan start-up, created a blockchain-based platform to auger trade collaboration among farmers, buyers, and service providers in Kenya. In January 2020, the company also raised USD$250,000 from Gray Matters Capital, to finance its planned future expansion to Malawi.

These blockchain platforms can also be used to connect farmers to other farmers, for activities such as asset or land sharing, resulting in more efficiency in economical farming operations. Blockchain platform can also enable small farmers to lease idle farms from their peers, thereby providing them with access to additional revenue sources, which they would not be able to do traditionally.

AgUnity, an Australian-start-up established in 2016, developed a mobile application which enables farmers to record their produce and transactions over a distributed ledger, offering a trusted and transparent platform to work with co-operatives and third-party buyers. The platform also enables farmers to share farming equipment as per a set schedule to improve overall operational and cost efficiency. In Africa, AgUnity has launched pilot projects in Kenya and Ethiopia, targeted at helping farmers achieve better income for their produce.

A Nigerian start-up, Hello Tractor uses IBM’s blockchain technology to help small farmers in Nigeria, which cannot afford tractors on their own, to lease idle tractors from owners and contractors at affordable prices through a mobile application.

Smart contracts to transform agriculture finance and insurance

Less than 3% of small farmers in sub-Saharan Africa have adequate access to agricultural insurance coverage, which leaves them vulnerable to adverse climatic situations such as droughts.

Smart contracts based on blockchain can also be used to provide crop-insurance, which can be triggered given certain set conditions are met, enabling farmers to secure their farms and family livelihood in case of extreme climatic events such as floods or droughts.

SmartCrop, an Android-based mobile platform, provides affordable crop insurance to more than 20,000 small farms in Ghana, Kenya, and Uganda through blockchain-based smart contracts, which are triggered based on intelligent weather predictions.

Netherlands-based ICS, parent company of Agrics East Africa (which provides farm inputs on credit to small farmers in Kenya and Tanzania) is also exploring a blockchain-wallet based saving product, “drought coins”, which can be encashed by farmers depending on the weather conditions and forecasts.

Tracking of assets (such as land registries) and transactions on the blockchain can also be used to verify the farmers’ history, which can be used by alternative financing companies to offer loans or credits to farmers – e.g. in cases when farmers are not able to get such financing from traditional banks – transforming the banking and financial services available to farmers.

Several African start-ups such as Twiga Foods and Cellulant have tried to explore the use of blockchain technology to offer agriculture financing solutions to small farmers in Africa.

In late 2018, Africa’s leading mobile wallet company, Cellulant, launched Agrikore, a blockchain-based digital-payment, contracting, and marketplace system that connects small farmers with large commercial customers. The company started its operations in Nigeria and is exploring expansion of its business to Kenya.

In 2018, Kenya-based Twiga Foods (that connects farmers to urban retailers in an informal market) partnered with IBM to launch a blockchain-based lending platform which offered loans to small retailers in Kenya to purchase food products from suppliers listed on Twiga platform.


Read our previous Perspective Africa’s Fintech Market Striding into New Product Segments to find out more about innovative fintech products for agriculture and other sectors financing in Africa


And last, but not the least, blockchain or cryptocurrencies can simply be used as a mode of payment with a much lower transaction fee offered by traditional banking institutions.

Improving mobile internet access to boost blockchain implementation

While blockchain has shown potential to transform agriculture in Africa, its implementation is limited by the lack of mobile/internet access and technical know-how among small farmers. As of 2018, mobile internet had penetrated only 23% of the total population in Sub-Saharan Africa.

However, the GSM Association predicts mobile internet penetration to improve significantly over the next five years, to ~39% by 2025. Improved access to internet services is expected to boost the farmers’ ability to interact with the blockchain solutions, thereby increasing development and deployment of more blockchain-based solutions for farmers.

EOS Perspective

Agritech offers an immense opportunity in Africa, and blockchain is likely to be an integral part of this opportunity. Blockchain has already started witnessing implementation in systems providing proof of ownership, platforms for farmer cooperation, and agricultural financing tools.

Unlike Asian and Latin American countries, African markets have shown a relatively positive attitude towards adoption of blockchain, a fact that promises positive environment for development of such solutions.

At the moment, most development in blockchain agritech space is concentrated in Kenya, Nigeria, Uganda, and Ghana. However, there is potential to scale up operations in other countries across Africa as well, and some start-ups have already proved this (e.g. Farmshine was able to secure the necessary financing to expand its presence in Malawi). Other companies can follow suit, however, that would only be possible with the help of further private sector investments.

Still in the nascent stages of development, blockchain solutions face an uncertain future, at least in the short term, and are dependent on external influences to pick up growth they need to impact the agriculture sector significantly. However, once such solutions achieve certain scalability, and become increasingly integrated with other technologies, such as Internet of Things and artificial intelligence, blockchain has the capability of completely transform the way farming is done in Africa.

by EOS Intelligence EOS Intelligence No Comments

Agritech in Africa: Cultivating Opportunities for ICT in Agriculture

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Agriculture technologies in Africa have been undergoing significant development over the years, with many tech start-ups innovating information and communications technologies to support agriculture at all levels. While some technologies have been successfully launched, some are in initial stages of becoming a success. Private sector investments have been the key driving factor supporting the development of agriculture technologies in Africa. In the first part of our series on agritech in Africa, we are examine what impact and opportunities arise from the use of these technologies in Africa.

Agriculture plays a significant role in Africa’s economy, contributing 32% to the continent’s GDP and employing 65% of the total work force (as per the World Bank estimates). Nearly 70% of the continent’s population directly depends on agribusiness. Vast majority of farmers work on small scale farms that produce nearly 90% of all agricultural output.


This article is the first part of a two-piece coverage focusing on technological advancements in agriculture across the African continent.

Read part two here: Agritech in Africa: How Blockchain Can Help Revolutionize Agriculture


Agriculture in Africa has been under the pressure of many challenges such as low productivity, lack of knowledge and exposure to new farming techniques, and lack of access to financial support, especially for the small-scale farmers. These challenges are prompting investments in newer technologies to enhance the productivity through smart agriculture techniques.

Lately, there have been an increased use of various technologies in agriculture in Africa, such as Internet of Things (IoT), Open Source Software, Cloud Computing, Artificial Intelligence, Drones/Unmanned Aerial Vehicles (UAVs), and Big Data Analytics. Many tech start-ups have developed solutions targeting various aspects of agriculture, including finance, supply chain, retailing, and even delivering information related to crops and weeds. These solutions are accessible to farmers through front-end devices such as smart phones and tablets, or even SMS.

Agritech in Africa - Cultivating Opportunities for ICT in Agriculture by EOS Intelligence

Start-ups lead agritech development in Africa

Many agritech start-ups in Africa have come up with solutions that have led to a rise in productivity of the farms. Drones have been a breakthrough technology, helping farmers oversee their crops, and manage their farms effectively. Drones use highly focused cameras to capture picture of crops, soil or weeds. This, coupled with big data analytics and Artificial Intelligence (AI), provides insights to farmers, saving their time and effort, while also helping them find potential issues which could impact the productivity of their farms.

There are various agritech start-ups that are developing such drones, and providing them to farmers for rent or lease to analyse their crops and farms. A South African agritech start-up, Aerobotics, offers an end-to-end solution to help farmers manage their farms using drones, through early detection of any crop-related problems, and offering curative measures for the problems using an AI-based analytics platform. The company partners with drone manufacturing companies such as DJI and Micasense to deliver these solutions.

Acquahmeyer, another start-up based in Ghana, also provides drones to its farming customers to help them use a comprehensive approach to apply crop pest control and plant nutrition management for their farms.

Advent of advanced technologies such as IoT is also helping farmers to adopt smart farm management through the use of smart sensors connected in a network. This helps every farmer to get granular details of the crops, soil, farming equipment, or livestock, enabling the farmers to devise appropriate farming approaches.

Kenya-based UjuziKilimo provides solution for analyzing soil characteristics using electronic sensor placed in the ground. This helps farmers with useful real-time insights into soil conditions. The solution further utilizes big data analytics to guide the farmers, by offering insights through SMS on their connected mobile phones or tablets.

Hello Tractor, a Kenyan start-up, provides an IoT solution, through which farmers can have access to affordable tractors which are monitored virtually through a remote asset tracking device on the tractor, sharing data over the Hello Tractor Cloud. Farmers, booking agents, dealers, and tractor owners are connected via IoT. The company is also collaborating with IBM to incorporate artificial intelligence and blockchain to their solutions.

AI has also witnessed a rapid growth in adoption across agriculture sector in Africa. Agrix Tech, based in Cameroon, has developed a mobile application that requires the farmers to capture the picture of diseased crop, which is then analyzed via AI to detect crop diseases, and helps the farmers with treatment solution to save their crops.

AI is also helping Kenyan farmers with the knowledge on planting the right crops at the right time. Tech giant, Capgemini, has teamed up with a Kenyan social enterprise in Kakamega region in Western Kenya to use artificial intelligence to analyze farming data, and then send insights about right time and technique of planting crops to the farmers’ cell phones.

There are other agritech solutions that include mobile applications which use digital platforms such as cloud computing to reach out to farmers, and provide them with apt agriculture solutions. Ghana-based CowTribe offers a mobile USSD-based subscription service which enables livestock farmers to connect with veterinarians for animal vaccines and other livestock healthcare services using cloud-based logistics management system. The company focuses on managing the schedules, and delivering the right service to the livestock farmers, to help them safeguard their animals from any health-related problems.

Several agritech investments are also impacting the financial side of agriculture. Kenya-based Apollo Agriculture provides solutions related to financing, farm inputs, advice insurance and market access through the use of agronomic machine learning, remote sensing, and mobile technology using satellite data and cloud computing.

Another Nigerian start-up Farmcrowdy has developed Nigeria’s first digital agriculture platform that provides financial support to the farmers by allowing those outside the agriculture industry to sponsor individual farms.

Several other agritech start-ups across the continent, such as Ghana-based Farmerline and AgroCenta, and Nigeria-based Kitovu have also launched data-driven mobile application for farmers. These technology solutions are proving to be a boon for agriculture sector in Africa, helping improve the overall efficiency and productivity.

Agritech in Africa - Cultivating Opportunities for ICT in Agriculture by EOS Intelligence

Agritech development is concentrated in Kenya and Nigeria

But, when it comes to first adopting the newest technologies and starting an agritech business in agriculture, Kenya and Nigeria have been leading in the adoption of new agritech solutions, accounting for a significant share of agritech start-up across Africa. Kenya has played a pioneering role in bringing agritech in Africa since 2010-2011, when the first wave of agritech start-ups began to bring new niche innovations. Currently, Kenya accounts for 25% of all the agritech start-ups in Africa, and the development is progressing rapidly, thanks to the country’s advancement in technology, high smartphone penetration, and relatively widespread internet access.

Similarly, Nigeria too has sailed the boat of success in agritech start-ups since 2015, and now it accounts for 23.2% of total agritech start-ups in Africa, with include major players such as Twiga Foods, Apollo Agriculture, Agrikore, and Tulaa. The growing inclination amongst Nigerian farmers towards using digital tools in agriculture sector has further pushed the rapid development in agritech sector in the country.

Other countries have also shown potential for agritech development, though it is still in the initial stages of becoming mainstream in their agriculture sectors. Ghana has encouraged several start-ups to launch different technology innovations for making agriculture more sustainable, while South Africa, Uganda, and Zimbabwe have also witnessed the rise in agritech start-ups over the years with newer technologies for agriculture sector.

Recent investments highlight the agritech potential

The agriculture technologies in Africa got the boost from the increased private funding. According to a report by Disrupt-Africa released in 2018, there has been a total investment of US$19 million in agritech sector since 2016. These investments have largely focused on funding agritech start-ups working on bringing innovative agriculture technologies. Also, according to the same report, the number of agritech start-ups rose by 110% from 2016 to 2018.

Some of the recent investments in the agritech sector include Kenya’s Twiga Foods, a B2B food distribution company, which raised US$30 million from investors led by Goldman Sachs in October 2019. The company aims to set-up a distribution centre in Nairobi to offer better supply chain services, while also expanding to more cities in Kenya, including Mombasa.

In December 2019, Kenya-based agritech start-up Farmshine, also raised US$25 million in funding from US-based Gray Matter’s Capital coLabs (GMC coLabs), to expand its operations in Malawi. GMC coLabs also invested US$1 million in another Kenyan B2B agritech start-up Taimba in July 2019. Taimba provides a mobile-based cashless platform connecting smallholder farmers to urban retailers. The investment was focused on strengthening Taimba’s infrastructure and increase the delivery logistics to cater to new markets.

Cellulant, a leading pan-African digital payments service provider that offers a real-time payment platform to farmers, also raised US$47.5 million from a consortium of investors in May 2018, which is the largest investment in the African tech industry till date. Cellulant also plans to channel a significant portion of funds into its Agrikore subsidiary, an agritech start-up dealing with blockchain based smart-contracting, payments, and marketplace system.

EOS Perspective

African agritech is expected to witness high growth in future. According to a CTA report on Digitalization for Agriculture (D4Ag) published in 2018, digital agriculture solutions are likely to reach 60-100 million smallholder famers, while generating annual revenues of nearly US$320- US$470 million by the end of 2020.

Adoption and use of innovative technologies such as remote sensing, diagnostics, IoT sensors for digitalization of agriculture is steadily moving from experimental stage to full-scale deployment, contributing to the data revolution in agriculture, while also unlocking new business models and opportunities.

Apart from these, blockchain is gaining prominence, and finding applications in the agriculture sector in Africa. This technology has the potential to significantly impact the agriculture sector, which we will discuss in the second part of our series on Agritech in Africa.

However, lack of affordability and knowledge to access such technologies, especially by small-scale farmers, has restricted the growth and reachability of these solutions. With the need to educate farmers and make such technology affordable and viable, it is likely that it may take at least 5-7 years before these technologies become truly mainstream in the continent.

A disparity of investments has been observed among the countries in the region. Over the years, countries such as Kenya, Nigeria, and Ghana have experienced a strong growth in terms of private investments, while other countries are left wanting. Investors have prioritized easy-to-reach markets in Africa, leaving behind the lower-income markets, resulting in agritech becoming less sustainable and scalable in these markets. However, several other African countries have shown the appetite to adopt agritech solutions, and offer significant potential.

This requires an intervention and participation from both governments and private investors, which can help improve scalability of agriculture technologies in the region. Implementation of farming digital literacy, public-private partnerships, and increased private sector investments in agritech enterprises can help the agritech industry experience a consistent and higher success rate, thus bringing the agriculture technology to a mainstream at faster pace.

by EOS Intelligence EOS Intelligence No Comments

Big Data Analytics: A Revolution for the Healthcare Sector

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Big data analytics is beginning to transform the healthcare sector by forging new pathways that lead to data transparency, reduction in healthcare costs, and improved patient outcome through better quality of healthcare services. Traditionally, physicians used their clinical judgment to make treatment-related decisions but over the last few years, the trend has shifted towards evidence-based decision-making by leveraging big data analytics, which correlates massive amount of data to provide quick analysis. Big data analytics is slowly changing the way data is managed, analyzed, and leveraged. Although the big data revolution is at an initial stage of its implementation in this sector and most of its potential for innovation and value creation is yet to be realized, it has already directed the healthcare industry on a path of rapid change and improvement.

In an era where healthcare data exists across different sources and formats – such as images, videos, texts, numerical data, etc. – such an enormous amount of data is incredibly complex and difficult to sort, organize, decipher, and manage. This is where big data analytics steps in. It aids in analyzing structured and unstructured data across multiple data sources, which helps to improve accuracy of diagnosing patient conditions and matching treatments with outcomes. Applying analytics in healthcare could reduce treatment costs, forecast outbreaks of epidemics, avoid preventable diseases, and most importantly, improve quality of life through better medical services.

Big data analytics has tremendous potential to cut down the spiraling healthcare costs. Analytics could be used to reduce preventable emergency room visits and hospitalizations, eliminate unnecessary lab tests, reduce inefficiencies, and avert security breaches and frauds, among others. Some key applications of analytics in healthcare include electronic health records (EHR), predictive analysis, real-time alerting system.

The EHR marketplace, part of big data analytics for healthcare market, in the USA is dominated by suppliers such as Epic Systems (a USA-based organization that develops software for healthcare sector) which held a market share of 22% in 2015. The EHR supplier landscape is consolidated at the top end, with three leaders (Epic Systems, Cerner, and Meditech) occupying majority share of 55% in the market in 2015.

Another segment of the big data analytics for healthcare, i.e. business intelligence market dealing with business intelligence tools support several major big data functions within hospital such as predictive analysis, clinical decision support, clinical workflow optimization, population health management, and financial performance modeling, is fragmented, unlike EHR. While Epic Systems occupies a sizeable portion of the business intelligence market (25% market share), over ninety vendors accounted for further 25% combined share of suppliers operating in the market in 2015.

EOS Perspective

For the longest time, healthcare has lagged behind other industries, such as banking and retail, in the use of big data. However, healthcare sector is now ripe for big data initiatives, which have the potential to completely transform the quality of healthcare services by offering a wide array of applications for predictive analytics, evidence-based accurate treatment decision-making, potential cure for complex diseases, improving clinical documentation, among many others.

For big data analytics to fully succeed, the healthcare industry must undergo few fundamental changes, so that the stakeholders can take advantage of big data. Some issues in the industry arise from resistance to change, as healthcare providers are accustomed to making treatment decisions independently, rather than relying on automation and analytics. Healthcare professionals need to shift from standard regression-based methods to more future-oriented techniques such as predictive analytics, machine learning, and graph analytics that can improve and quicken decision-making and treatment-related judgement.

Other obstacles are structural in nature – several healthcare professionals have chosen to underinvest in information technology because of unsure returns. Additionally, some hindrances stem from the nature of the healthcare sector itself. With presence of several players in the industry, it is not easy to share data with different providers or facilities due to privacy concerns, which hinders the use of analytics on data sets.

Currently, implementation of big data technology in healthcare is limited and mostly concentrated in the USA, largely due to the high infrastructure costs and hefty initial investment. Furthermore, the human expertise required to leverage healthcare analytics lags behind. Nonetheless, healthcare professionals are beginning to understand the value of leveraging volumes of patient data and efforts are being made to overcome all barriers.

Healthcare professionals are beginning to understand the value of leveraging volumes of patient data and efforts are being made to overcome all barriers.

Big data has the potential to completely revamp the healthcare sector, in the same way it has transformed several other industries. Besides reducing costs, big data initiatives could save many lives and improve patient outcomes. Pharmaceutical industry experts, payers, and providers are slowly starting to analyze big data to obtain insights. Although such efforts are in the preliminary stages, collectively they could help the industry to tackle issues such as variability in quality of healthcare and growing healthcare spend. Healthcare stakeholders who decide to invest in data capabilities and promote data transparency will not only achieve a competitive edge but will also lead the healthcare industry into a new era.


*Brief description of healthcare organizations – refer to the infographic

  1. USA-based healthcare organizations – MemorialCare Hospital, Parkland Hospital, Beaufort Memorial Hospital, Kaiser Permanente, Emory University Hospital, and UnitedHealthcare
  2. Israel-based organization providing technology/analytical solutions for the healthcare sector –Zebra Medical Vision
  3. USA-based companies providing software, hardware, and technology solutions and services for the healthcare sector – Epic Systems, Cerner, and Meditech
  4. USA-based provider of information technology solution, owned by Xerox – Affiliated Computer Services
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Five Technology Trends to Reshape Retail in 2017

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Today, retail and technology have become inseparable, driven by the need to digitalize services to offer convenience to shoppers and elevate their shopping experience. Retailers are slowly shifting focus towards being phygital, and to digitalization of in-store experience, supported by disruptive technologies (social, mobile, cloud, and analytics) continuously transforming the face of retail sector.

Besides enticing customers and creating a unique shopping experience, digital retail integration is increasingly simplifying supply chain management, payment systems, and tracking of inventory and sales data, among others. Some retailers are using technology to get insights into hard-to-capture customer behavior data, which is then used to take effective measures to improve sales.

Clearly, technology has become an indispensable means to empower the retail sector and will continue to do it in 2017 with innovations such as Internet of Things (IoT), smart mirrors, big data analytics, chatbots, robotics, etc., sweeping every possible domain of retail.

By the end of 2017, insights captured using big data analytics will be increasingly used by retailers to devise business strategies, which is likely to help them to stay abreast of retail trends. Big data analytics are expected to play a key role in predicting sales and trends, conducting consumer sentiment/behavior analysis, forecasting demand, achieving price optimization, and devising customized promotions.

Interactive mirror, a smart mirror that helps to virtually try-on clothes, is an interesting digital retail innovation, which is likely to gain more popularity in 2017. Interactive mirrors’ application can be customized according to the needs of individual retailers. For example, companies such as Ralph Lauren (a US-based retailer) are using these mirrors to show consumers how a particular outfit will look during different times of the day by changing the lighting of the fitting room along with providing suggestions on accessories, which are displayed on the mirror, to encourage more purchase. Companies such as Lululemon (a Canadian athletic apparel retailer) are using interactive mirrors to suggest places to exercise and provide information on healthy living. These mirrors are not only a means to attract shoppers by offering unrivaled shopping experience, but can also be used to gather consumer behavior data. With the help of interactive mirrors, Rebecca Minkoff (a US-based luxury retailer of handbags, accessories, footwear, and apparel) store was able learn that a leather jacket was tried on 70 times in a week but never purchased. Most shoppers asked for different sizes using the interactive mirror, indicating that there was a fit issue.

Chatbots, another invention to continue gaining traction throughout 2017, act like a virtual concierge service, guiding customers through the shopping process, providing detailed information on product and stock level, and allowing shoppers to place an order and track it in real time. Chatbots are also a great tool for retailers to get insights on shoppers’ tastes and preferences – for instance, all first-time shoppers on Sephora’s (a French cosmetics manufacturer) chatbot are required to take a short quiz that helps the bot know about personal preferences of a user – this information is used to recommend products. The bot also provides reviews on certain products.

In 2017, IoT is likely to become an integral technology for the retail sector to build smart stores. IoT’s significance is expected to grow in retail with about 70% of retailers in the USA ready to adopt the technology in 2017, according to a survey conducted by Zebra Technologies. IoT will be the key to interconnect in-store smart devices and sensors with Internet, which will enable better data-driven business decisions and ease of operation.

For the past couple of years, big box retailers such as Staples, Walgreens, Amazon, and Gap have been using robots for warehousing and logistics operations, but 2017 is expected to witness an increasing implementation of robotics for customer facing in-store operations as well. While use of robotics for distribution center operations will still hold importance, the launch of Amazon Go stores, Amazon’s robot-powered supermarkets, Lowe’s customer-assistance robots, etc., will increase foothold of robotics in front-end tasks such as customer assistance (we wrote about Amazon’s latest efforts to digitalize the grocery market it in our publication Amazon: Prepared to Digitalize Grocery Business in the USA? in April 2017). In the coming 5-10 years, robots can be expected to become an integral part of the complete retail value chain including both front-end and back-end operations.

Five Technology Trends

EOS Perspective

In the medium term, in-store shopping is not going to fade away due to competition from online retail, but instead it is likely to witness an upgrade with retailers enthusiastically integrating technology into physical stores. The key focus of all retailers in 2017 will be to enhance personalized customer interaction, offer innovative in-store experience that rivals the convenience of online shopping, and use the gathered insights on customer shopping patterns to conduct effective predictive analysis. To achieve these objectives, retailers are likely to use technologies such as big data, IoT, and robotics, and employ interesting innovations such as chatbots and smart mirrors to offer seamless services to attract customers as well as use these innovations to capture valuable insights on consumer behavior.

Over the years, technology has tremendously contributed to the success of retail sector – starting from browsing, point-of-sale, shipping, checkout, supply chain, to payments, and so much more. This will not change in 2017, as technology will continue to digitalize retail, with top retailers prioritizing technology to improve sales.


*key sector of operation for each retailer included in the infographic

  • General merchandise: Amazon, Tesco, Macy’s, Kohl’s, and Kroger
  • Footwear: Nike
  • Fashion (apparel, fragrance, cosmetics, sunglasses, handbags, shoes, etc.): Burberry, Rebecca Minkoff, Nordstrom, Sephora, Van Heusen, H&M, and Ralph Lauren
  • Electronics: Anker
  • Online retailer: eBay, Ocado
  • Food: Godiva
  • Home Improvement/appliance: Lowe’s
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