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120 AI Predictions For 2019

Me: “Alexa, give me a prediction for 2019.” Amazon AI: “The crystal ball is clouded, I can’t tell.” My conversation with Amazon’s “smart speaker” or “intelligent voice assistant” just about sums up the present state of “artificial intelligence” (AI) at home, the office, and the factory: Try a few times and sooner or later you will probably get the correct action the human intelligence behind it programmed it to perform.

To deliver effective Self-Driving Finance, financial institutions will require specialized forms of AI for each of their customer segments such as retail, small business, and wealth—moving away from more generic forms of AI towards domain-specific solutions that embed subject matter knowledge and expertise”—David Sosna, Co-founder and CEO, Personetics “2019 will be the year of specialized AI systems built by organizations based on their own data.

Similar to using a GPS such as Waze when you're driving to unlock optimal routes depending on the time of day, AI will unlock how each employee can best use a system, providing a range of possibilities based on what the individual needs to do”—Rephael Sweary, Co-founder and President,WalkMe 'In 2019, we will start to see technology that will allow designers to talk to computer programs powered by AI to redesign, optimize and lightweight parts made by 3D printers in real time.

More power will be put into the hands of designers who will be better able to test and experiment with alterations to create optimal designs much faster than before”—Avi Reichental, Founder and CEO,XponentialWorks “Because of cloud and the pervasiveness of APIs, in 2019 we’ll begin to see AI deliver meaningful value to the enterprise and get us closer to the Holy Grail of AI, which is helping people at all levels of an organization do what they do more effectively and efficiently, while uncovering new opportunities and new ways to work”—Josh James, Founder and CEO, Domo “While B2B providers have been slow to adapt to the high standard of personalized digital experiences set by Amazon and Google, the industry has at least acknowledged the value of personalized home and landing pages.

As customer expectations increase, enterprises will need to keep pace by using machine learning and AI to offer a personalized experience beyond the first impression, which extends to other assets such as technical documentation, community portals, and chatbots”—Gal Oron, CEO,Zoomin “In 2018 we saw a great deal of hype around AI in healthcare but we also saw it become a reality—in everything from predictive analytics for chronic disease management, to workflow enhancement in radiology as well as administrative and financial use cases that bring operational efficiency.

Instead, automation should primarily be leveraged pre-breach, serving as a proactive defense mechanism to help organizationsoutmaneuverthe attacker at the earliest stage and minimize the potential damage”—Nadav Zafrir, CEO, Team8 “Robotics and AI are increasingly used hand-in-hand to inspect and ensure the proper functioning of critical infrastructure that our society is built on—power lines, railroad tracks, flare stacks etc.

Today’s cloud systems that remotely control Industrial IoT and AI - often at significant distances from inspection sites - will begin transitioning to distributed and autonomous systems closer to the source of inspections, making inspection data collection more efficient and safer”—Ashish Jain, Managing Director of Data Sciences, GE Ventures “Artificial Intelligence (AI) and Machine Learning have been hot topics for a while, but that will begin to decline in 2019.

We will no longer associate AI with futuristic robots and self-driving cars, but rather productivity tools and predictions to help everyday menial tasks”—Josh Poduska, Chief Data Scientist, Domino Data Lab “2019 will be the year of the death of the data scientist.In 2019, everybody is going to start learning Artificial Intelligence (AI) and the domain of data science will no longer be a purist data scientist.

From agritech and crop optimization to utilities and alternative energy, the big data analytics and machine learning behind AI will be leveraged to completely change the way consumers interact with their surroundings”—Natan Barak, CEO and Founder,mPrest 'In 2019, the global lending sector will see an uptick in AI that can predict financial eligibility and funding opportunities.

The Autonomous Vehicle industry will move away from object fusion and towards raw data fusion, which enables AVs to better interpret movement, speed, angle, and trajectory, and provides rich data to predict the direction and future movement of an object, pedestrian, or vehicle”—Ronny Cohen, CEO and Co-founder, VAYAVISION “Multi-trillion-dollar markets such as commercial real estate are comprised of an intricate web of interactions that affect every decision, and AI technology is now mature enough to tackle these highly complex transactions.

CTO,Tactile Mobility 'As more businesses rely on AI to fuel their own products, services and data-driven marketing innovations, bad actors across the digital ecosystem will utilize similar capabilities to increase their efforts and execute massive fraud schemes, resulting in hundreds of millions of dollars in losses for brands and marketers.

With that, companies that invest smartly in AI and machine learning-based fraud protection tools will be able to clearly ‘see’ the entire ecosystem and protect themselves from fraud and the polluted data that impacts business decisions—leading to a significant competitive advantage'—Ran Avrahamy, VP, Global Marketing,AppsFlyer “AI research and applications are proving increasingly important in healthcare, improving patient outcomes through a more personalized, data-driven approach.

Just as big data is used to curate more satisfying user experiences, more granular ‘small data’—information generated by each individual andanalyzed by AI tools, turning smartphonesand consumer wearables into powerful at-home diagnostic and treatment tools—will be usedto drive digital health users to action based on their real-worldbehavior, capabilities andneeds, and to boost population health by making disease predictionand preventionscalable.

In 2019, AI will be the linchpin of digital health’s application to the prevention and treatment of disease, specificallychronic illnesses,connecting the dots between the small data that can optimize an individual’s personal care and the big data that can uncover solutions with a global impact”—Dana Chanan, CEO and Co-Founder,Sweetch “2019 will be a pivotal year in the way cities understand their urban mobility ecosystems in order to build much more efficient transportation systems throughout urban areas.If today’s cities are primarily focused on severe challenges such as traffic, pollution and lack of parking space, in 2019 they will have far better visibility into the root cause—inefficiency of movement in urban areas.Understanding how people are moving in urban areas, from where to where, when, with which means of transportation, and understanding why—that’s the core that will allow cities to build more efficient mobility, reducing our need to move around, encouraging people to move together, and creating multimodality.

This data will remain key to informing the bulk of marketing strategy for years to come'—Chase Buckle, Senior Trends Analyst, GlobalWebIndex “The hype around AI technologies that match human intelligence in some abstract form is drowning out the fact that today, there is real value in AI tools that collect, organize and make actionable the collective human experience.

Currently, we have a variety of technologies that offer a compelling vision of the future, but that vision is impeded by the fact that the devices are isolated, lacking context, and are thus unable to act autonomously: the consumer must still supply the intelligence for the ‘smart home.’ The mating of RF sensing technology with mesh and other networking schemes will amplify the value of network hardware, enabling them to provide powerful communications infrastructure and sensory feedback—the necessary convergence of control and communications needed to create cognitive systems.

The ability to understand human emotions and cognitive states will become part of the criteria for evaluating AI, as companies make decisions on which AI solution to select for their workplace, and even as consumers decide between systems like virtual assistants or smart speakers to have in their homes”—Rana el Kaliouby, PhD, CEO and co-founder, Affectiva “The focus of AI will shift from intelligence to empathy—we’re moving beyond the point where basic intelligence suffices for consumer-facing AI, as customers want to know that they are being viewed as individuals and not just as customer data records.

At the same time, the current misconception about all data analytics being AI will be more widely discussed, particularly with regards to the availability of sufficient, relevant and specific data to train algorithms and keep them ‘learning.’ This will lead to an increased focus on more advanced methodologies that can learn and adapt based on actual real-time data”—Mikael Johnsson, Co-founder, Oxx “Because companies are recognizing that AI cannot be built without high-quality data, they will increasingly turn to specialized providers that sit on crucial data resources to help them understand their unstructured data.

Eventually, uses will include AI-defined network topologies and basic operations, which will help us forge a network that runs on auto-pilot”—Kailem Anderson, Vice President of Software and Services, Ciena “The explosion of artificial intelligence (AI) within IT is poised to provide many benefits and time-saving opportunities in 2019 but will require IT decision-makers (ITDMs) to evolve into strategic consultants rather than serving in reactive roles.

We won't see autonomous cars that never crash but AI will augment workplace productivity in new and interesting ways in 2019”—Ram Menon, Founder and CEO, Avaamo “2018 was the year of bots, and over the next year we’ll see pervasive analytics and intent-based AI take this a leap further, highlighting the importance of specialized service desks that streamline IT support management and allow for instant knowledge delivery”—Phani Nagarjuna, Chief Analytics Officer,Sutherland “AI and machine learning (ML) have been the ‘silver bullets’ of the security industry for the past few years.

With the growing reliance on large datasets, AI systems will need to guard against such attacks data, and the savviest advertisers will increasingly look into Adversarial ML techniques to train models to be robust against such attacks”—Prasad Chalasani, Chief Scientist, MediaMath “AI will add an extra layer of predictability, allowing organizations to see patterns and gain insights from IoT devices and past customer behaviors—ultimately making supply chains smarter, leading to faster, more efficient production and fulfillment, and happier customers.

In 2019 and beyond, we can expect AI to take supply chains from reactive in nature to prescriptive levels, helping companies get one step ahead of consumers’ rising expectations”—Hala Zeine, President of Digital Supply Chain, SAP “In 2019 AI will ‘cross the chasm’ in healthcare as mainstream non-pioneering institutions apply AI-fueled clinical decision support tools to everyday work, including radiologic analysis in the U.S. and oncology drug selection in Africa and South America.Additionally, as advances in molecular biology demonstrate that many ‘common’ diseases are actually clusters of rare sub-forms, AI will find the high-value pockets of small data (such as unusual genetic signatures) hidden in vast reams of big data”—Frank Ingari, Board Member, Quest Analytics “AI for customer self-service isn’t as successful (yet) as the hype would indicate.

Many organizations in 2019 will take a split approach—more aggressive use of AI to automate repetitive agent after-call work and a more targeted approach with simple and high-volume self-service use cases”—Chris Bauserman, VP of Segment and Product Marketing, NICE inContact “The key word is cognitive load and how do companies reduce it by providing better guidance and overall automation that helps make it easier to use—RPA (Robotic process automation) is a great example of this and continues to heat up.

In 2019, we can expect to see more widespread introduction of software robots and artificial intelligence (AI) workers as organizations look to leverage automation to enhance their overall commerce ecosystem”—Rob Maille, Head of Strategy and Customer Experience, CommerceCX “As artificial intelligence applications grow in popularity, one key enabling technology will be the ability to process larger data sets constantly being updated with operational data.

Heading into 2019, businesses should be looking to security in AI, using emerging technologies as a way to protect their customers—both from a purchasing standpoint and from potential digital threats that seek to steal the information customers are sharing with brands”—Dan Kiely, CEO, Voxpro “Intelligent robotic process automation will emerge as business critical, as companies will require the high automation level necessary to become intelligent enterprises in 2019.

In 2019 we’ll see an increase in health wearables hitting the market that use AI to track a vast number of conditions like blood pressure, painting a more holistic picture of a person’s health, as it changes in real-time”—Kevin Hrusovsky, CEO, President and Chairman, Quanterix “Many AI-enabled automation projects in 2018 failed because they were targeting the wrong processes to automate.

Ontologies add an additional tool to the set of approaches that companies can now deploy off the shelf and ontologies ability to link together diverse sets of data and draw conclusions from them, make an ontology-based system an easy start for enterprise and business organizations in 2019”—David Keane, Co-founder and CEO, Bigtincan “Enterprises have been so focused on the potential benefits of AI, that it’s become more buzz phrase than reality.

Gradual rollout after testing will help mitigate any major disruptions to everyday business, while enhancing the organization’s future technology footprint”—John Samuel, Senior Vice President, Global Chief Information Officer, CGS “We will see a huge spike in the exploration and adoption of ML/AI tools that can help develop mobile and web test scenarios without coding (codeless testing), to speed up the process of code validation and to provide a greater stability for the test code.

On the front of smart decision making and quality analysis, we will see ML/AI solutions that can automate the slicing and dicing of data, and quickly provide root-cause analysis for issues that were detected during the DevOps pipeline testing activities”—Eran Kinsbruner, Director, Lead Software Evangelist, Perfecto “2019 will see an exponential increase in the number of research projects and companies building solutions that leverage AI to increase developer productivity.

This shift will increase productivity and safety and will open the doors for new business models throughout the industry, like Outcome-as-a-Service”—Saar Yoskovitz, Co-Founder and CEO, Augury “The biggest benefit of AI will turn out to be something that we think of as quintessentially human: being ‘good team players.’ While previous years have focused on individual algorithms doing things better than individuals, 2019 is about collections of algorithms starting to collaborate on complex tasks.

they will reverse the current trend—growth of drug development timelines by 25%, reaching a startling 12 years on average—and bring much-needed therapies to the market sooner”—Isabelle deZegher, Vice President, Integrated Solutions, PAREXEL “In 2019, society will push for the demystification of AI and demand a better understanding of what technology is being built, and greater transparency into how it is being used.

On the vendor side, technology providers will make AI tools and platforms easier to implement and put in place, and the difference between technology leaders who can truly create this change within an organization and those who are trying to capitalize on the hype will become more and more vivid”—Connie Schiefer, VP Product Management, Mya Systems “For the last two decades, the epicenter of the world’s economy has shifted as technology driven companies take over entire markets at the cost of businesses like Sears.

While the technological aspects of this process overhaul will be what drives the necessary sea change, we’ll come to realize that an even larger opportunity lies in using advanced technologies to optimize human behaviors anywhere they intersect with business process flow”—Alan O’Herliy, CEO, Everseen “In 2019, we’ll stop doubting humans’ role in the fourth industrial revolution—nor fear they don’t have one.

However, we may see more widespread adoption of AI to reduce the amount of time recruiters spend on mundane tasks so they can use their time on more meaningful candidate interactions”—Kurt Heikkinen, CEO, Montage “We expect to see AI used more in higher education in 2019 as institutions continue their digital transformation journeys and look to appeal to students’ preferences for adaptive, engaging learning experiences.

To increase the adoption of AI, AI platforms will need to empower traditional developers with tools to enable them to create machine learning models faster, as well as ensure they have an integrated platform that will allow developers to annotate and label the data needed to improve the accuracy of their models”—Dale Brown, VP of Business Development, Figure Eight “The biggest threat to US and Europe is the rapid advances in AI coming out of China.

It also provides retailers with an opportunity to check their data—and any public or aggregatedatathey pull in—to ensure AI isn’t making bad assumptions under the adage ‘garbage in, garbage out’”—Nikki Baird, Vice President of Retail Innovation,Aptos “With an increasing availability of Artificial Intelligence (AI) capabilities driven by cloud computing, AI will make its way into video conferencing in 2019 in everything from meeting room activity analysis and efficiency, understanding participants’ reactions to given messaging, automated joining procedures, and platform utilization.

As organizations seek to optimize their services and work more efficiently, it’s only natural that AI, now readily accessible to assist with predictive analysis and turning data into actionable insights, will transform conferencing and collaboration as we know it”—Jordan Owens, VP of Architecture, Pexip “We will in the near future see the lines between audio content and written content disappear.

As voice assistants and search algorithms continue to advance, you will soon be able to have a human-like conversation with your assistant, who has instant access to all the knowledge in the world”—Johan Billgren, Co-founder and Chief Product Officer,Acast “In 2019, I predict that it will become clear that the information and analytics systems that are on the bleeding edge of creating and policing truth—particularly AI-based technologies—are themselves part of the ‘bias’ problem.

This will lead to the start of a fundamental shift in how we think about truth—not in binary terms—but as points on a spectrum, with underlying information systems and analytics systems under fire for their inability to either measure or enforce the integrity of their underlying data sets and analytics methods”—Kris Lovejoy, CEO,BluVector “I expect 2019 will be the year we’ll see an explosion of production applications leveraging artificial intelligence.

As the ML/AI buzz continues to wear thin, we’ll see a strong appetite emerge for this type of impact-driven technology and behavioral metadata among organizations”—Aaron Kalb, VP of Design and Strategic Initiatives and Co-founder, Alation “Last year was the year of the data scientist—enterprises focused heavily on hiring and empowering data scientists to create advanced analytics and machine learning models.

This involves creating in-depth AI development, testing, DevOps and auditing processes that enable a company to incorporate AI and data pipelines at scale across the enterprise”—Nima Negahban, CTO and Co-founder, Kinetica “AI will fundamentally automate the order-taking side of sales and empower successful reps to becomeconsultants to buyers, helping both parties discover the critical resources needed to inform their buying and selling decisions.

While creative teams and designers will still determine the aesthetic and tone for a given piece of content, their role becomes even more crucial as the designers of generative frameworks, determining which elements in an experience to make flexible while still maintaining the core of the creative concept”—Claire Mitchell, Director, VaynerSmart “While 2018 saw many retailers and brands gain more familiarity with AI and its potential use cases, 2019 will see those applications put into practice.

Video AI will be a great example of this, helping turn physical settings into actionable data that companies in retail and other sectors can utilize to strengthen customer experiences like never before—and unlock new services and customer value they may not have even thought about bringing to market”—Michael Adair, President and CEO, Deep North “Personalization has long been the holy grail for marketers and everyone agrees results improve by knowing what customers care about and engage with.

I think we’ll also see AI-based digital assistants more front-and-center for new employees, taking a larger role in processes like onboarding or skills training”—Gretchen Alarcon, GVP of HCM Strategy, Oracle 'One of the biggest challenges in translating lab performance into the clinical setting is the ability to consistently replicate results over time, location and assay—hence the need for rock-solid quality systems and standards that provide quantifiable reliability over cohorts.

When applied properly, streamlining and expediting this process ensures that any variability in the workflow—from the sample collection, processing, and all the way to instrument ingestion—is drastically minimized and hence the results become supremely reproducible, and where potentially actionable and clinically relevant information is derived in mere seconds”—Aldo Carrasco, CEO, InterVenn Biosciences “Our fascination with the use of computing power to augment human decision-making has likely outgrown even the tremendous advances made in algorithmic approaches.

Soon we can expect to see this concept evolve into a new class of cybercrime in which malicious content is automatically generated by AI algorithms—a new category we define as ‘DeepAttacks.’ DeepAttacks can manifest themselves at scale by generating code within malware files, creating fake network traffic in botnets, or in the form of fake URLs or HTML webpages.

We’re seeing this technique emerge in discussions at NeurIPS and in some public solutions already, such as Microsoft SEAL and HE-Transformer, and expect innovations around AI privacy and encryption to explode next year”--Casimir Wierzynski, Senior Director, Office of the CTO, Artificial Intelligence Products Group, Intel 'AI will make a huge impact on cybersecurity by increasing exponentially the ability to detect rogue patterns and foul play, and in time will improve significantly on human ability to analyse data effectively, which will lead to even faster detection and response capabilities via machine learning.

To drive the false negative rate close to zero, an unacceptably high rate of legitimate activities would have to get blocked”—Richard Anton, Co-founder, Oxx “In the automotive world, leadingautomakers and component suppliers are constantly looking for differentiation throughAI, and as a result, there iscurrentlya major shift underway from the rigid hardware solutions that started theAIrevolution to more flexible,software-based onesthatcan be easily tailored to customer needs.In 2019 and beyond, AI will increasingly existon the edge, as concerns around privacy, security and latency make edge-AIpreferableover the traditional approach that relies on centralizedAIsystems.Manufacturers, however, are struggling with the consequences of addingAIto their edge-based products, mainly due to the expensive, bulky and power-consuming hardware required for runningthem.

Artificial Intelligence (#AI) and #Sustainable #Food Systems – help or hindrance? | Geoff Tansey blog

Last month, the day after the world’s scientific academies warned that global food systems are failing humanity and speeding up climate change, I was at a workshop at Chatham House on “Artificial intelligence for a sustainable and healthy food system“.

We heard about the many ways in which artificial intelligence is being used today – with over a hundred companies working on areas such as robotics and roles, precision agriculture and predictive analytics, farm management software, smart irrigation, plant data and analysis, animal data, and next-generation farms.

That needs to go along with better policy-making governance frameworks to tackle the unacceptable levels of malnutrition and promote healthy food production and consumption, as the 2018 global nutrition report, released around the same time as the workshop, points out.

It also suggests that precision farming, while holding out the prospect of increased efficiency, may also lead to a growing digital division between small and large farms, severe informational asymmetries and a dependence on off-farm service support, abuse of data by agricultural commodity markets, undermine the autonomy of the farmer and local farming structures, and lead to an unprecedented power shift in the industrial farming process.

For all the various promise technological innovation offers, in the end the question is what kind of world we want it to lead to and which scenarios will most clearly lead us to one in which we can achieve sustainable development goals, have more varied diets and farming systems in which less agricultural efficiency, as currently defined, could actually mean more system efficiency and lower waste.

Oil Gas 4.0: An inside look at the oil and gas industry’s tech-driven effort to power tomorrow’s economy

This year, humankind quietly passed a historic turning point: As of September, more than half of the world’s population—roughly 3.8 billion people—now live in middle-class households.

The “Oil & Gas 4.0” mission is built on the recognition that the oil and gas industry will continue to play an expansive role in the energy required to drive the 4th industrial revolution and must embrace disruptive technologies in order to enable this massive step change in human development.

While best-known for its use in cryptocurrency, blockchain unlocks new ways for oil companies to, for example, track shipments and draw up “smart contracts” that only take effect when pre-determined conditions are met.

“The big U.S. West Coast tech major companies are engaged in a way that they never have been before owing to Oil & Gas 4.0 and the massive opportunities with artificial intelligence, machine learning, and big data,” Yergin said.

For example, using seismic waves, geophysicists can scan features deep underneath the earth’s surface, letting them create intricate 3D models of potential energy sites.

“We believe that the 4th industrial age will see capability move from ‘scale economies’ to ‘insight economies’ as the ability to forecast, anticipate, and prepare for change becomes automatic and routine,” said Luq Niazi, global managing director of chemicals and petroleum industries at IBM.

Ultimately, the companies that have become enlightened by the great strides made in technology innovation will create capabilities to generate more energy more efficiently to serve the needs of the growing population and middle classes.” The oil and gas workforce is aging: As of 2016, the average age of offshore workers was 42.7, an increase from 40.7 in 2014.

Recognizing the responsibility that the industry has towards the environment, many companies, have taken steps to reduce greenhouse gas emissions, research lighter and recyclable plastics, and invest in renewable energy.

(The world’s 17 large-scale plants that use the technology collectively capture 40 million metric tons of carbon dioxide annually.) Technology also plays a key role in sustainability, according to Accenture managing director Tracey Countryman, who focuses on the oil and gas industry.

While the internet and digital technology have made it easier for people to connect and collaborate, the oil and gas industry has traditionally remained fragmented—not just between companies, but within individual business units.

In January, 90 companies agreed to participate in an industry-wide effort to bring blockchain to the global supply chain, giving companies real-time shared access to key shipping data such as temperature and location.

As demand for energy and its products continues to climb, the onus is on energy companies to partner up in an effort to reduce costs, share knowledge, and invest in key technologies to meet the world’s needs.

Artificial Intelligence and the coming of the self-designing machine

Manufacturing is in the early stages of a state of disruption brought on by technologies such as artificial intelligence (AI) and 3D printing. 'Additive manufacturing' has already worked itself into companies such as Porsche and Bugatti, and aircraft builder Airbus is experimenting with UAV THOR, a drone made entirely of 3D-printed parts.

“In an AI-driven generative design paradigm, humans input design goals and material parameters,” explains Avi Reichental, the CEO and founder of XponentialWorks (a venture investment, corporate advisory, and product development company specializing in artificial intelligence, 3D printing, robotics, and digital transformation).

This includes designs that are stronger, lighter and use less material than would be used otherwise to save money, increase scalability, and raise efficiency while enhancing form and function.” In this increasingly connected manufacturing chain, a product’s form and features don't even need to be finished when it ships.

“For example, a robot on Mars might detect very loose sand and determine it cannot move about efficiently to complete its mission,” explains Ben Schrauwen, co-founder and CTO of Oqton, an autonomous manufacturing platform. “The robot could learn to suggest different modalities on how to move in that environment, and, with 3D printing technology and some local robotics, it's very conceivable that the robot could reconfigure itself at a distance to continue its mission unimpeded.” Interplanetary travel and space missions aside, there is plenty of motivation to enable things to co-design or self-design here on Earth, too.

“The most exciting change is the embedding of sensors within manufactured items to create a design system that is a self-improving circuit, where the sensors provide feedback to the design to cause it to respond and improve,” said Tod Northman, partner at Tucker Ellis, a law firm with a specialized practice in intellectual property and liability issues concerning autonomous vehicles and other artificially intelligent devices. “Such a system will become a self-improving loop, with better products resulting without human intervention.'

Is Your Supply Chain Ready for Alexa? Artificial Intelligence? Autonomous Vehicles?

Autonomous trucks already speed down Nevada’s highways, and drones now deliver packages in China’s most remote villages.

Over the past decade, consumer products executives thoughtfully reinvented their supply chains to emphasize long, mass runs in standardized manufacturing facilities, aiming to lower costs and prices.

Now, those same business leaders face the challenge of overhauling their supply chains again, this time for a world being transformed by massive technology disruptions, as well as by the rising retailer demands and consumer expectations those technologies have created.

Company survey of 51 consumer products executives, we learned that 88% expect their supply chain and operations activities to feel the impact of digital technologies in the next five years, up from 66% just last year (see Figure 1).

Designing to win means painting a scenario in which the company produces its ideal product portfolio with the most collaborative supplier base, employing a perfect labor model and state-of-the-art production equipment, and delivering it via the optimal route to the customer.

The future scenarios need to take into account shifting ecosystems and profit pools, evolving consumer behavior and preferences, disruptive technologies, and new competitors and business models.

To illustrate the best strategies for supply chain reinvention, we’ll explore how companies can take a today-forward and future-back approach to three of these emerging technologies: artificial intelligence (AI) and machine learning, Alexa and voice ordering, and autonomous vehicles and delivery.

Increasingly, consumer products companies are using these technologies to squeeze inefficiencies out of their supply chains—ensuring that the right inventory is in the right place at the right time, for example, or reducing manufacturing costs with predictive maintenance intelligence.

When one company saw how its inaccurate demand forecasts led to excessive returns, it built a machine learning platform that drew on historical order and returns data to continuously improve demand forecasts at the SKU and store levels.

In the decades ahead, meal consumption will look vastly different, with companies using AI to create highly customized meals that consumers either buy online for delivery or purchase in supermarkets.

Meanwhile, companies like wellio are using artificial intelligence to provide customized meal suggestions based on personal health and taste preferences, selected recipes and ingredients consumers have on hand—gathering and interpreting data over time to further understand home chefs’ preferences.

As these shifts play out over the next 10 to 15 years, brands will need to reconfigure legacy supply chains that were built for mass scale, creating new models capable of handling both mass scale and customization.

And they will move to much more flexible manufacturing systems, including designing and running smaller manufacturing lines—in some instances, even adopting an extreme asset-light model, outsourcing all manufacturing to nimble third-party manufacturers.

Another big step they are taking: adopting specialized labeling and shipment-friendly packaging to improve operational efficiency and the consumer experience (measured through a combination of user reviews and user returns).

Some are also considering new pathways to shoppers, such as direct-to-consumer businesses, that will help them stay relevant by generating valuable customer data, thus gaining a defensible position against the Amazons of the world.

The company began providing differentiated levels of service based on the importance of the customer as well as its ability to collaborate for mutual gain.As a result, it expects to deliver best-in-class on-time/in-full delivery to priority customers while reducing inventory by 20% and lowering total network costs by nearly 15%.

“Earlier this year we introduced a range of new razor products and declared that ‘one size’ does not fit all men when it comes to razors,” said Pankaj Bhalla, P&G’s director for Gillette and Venus North America, in an online statement, adding that the pilot program furthers the company’s commitment to place power in the hands of consumers.

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