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Artificial Intelligence to Achieve Net-Zero in Food and Beverage

The facts of life are such that everyone has to eat and drink in order to survive. However, in a time where consumers are much more aware and selective of the Food & Beverage providers that they purchase from, the strain is being felt by suppliers of those products. The Pandemic also has made the industry even more volatile and it has become critical to ensure the supply chain remains uninterrupted.

Now, more than ever, consumers are requiring transparency regarding ingredients and health and safety considerations of all their food and beverage purchases. Many consumers don’t care solely for what their food and drinks are made of, but also about the Environmental, Social, and Corporate Governance (ESG) objectives of the providers and how these corporations are executing against these objectives.

Consumer interest in sustainable food choices increased by 23% in 2020 with less concerns regarding health and an increase in concerns around climate change, waste and recycling. Source: Tastewise

With consumers and suppliers demanding higher standards from the Food & Beverage industry, it is a daunting task to remain competitive in today’s market. However, with the implementation of Artificial Intelligence solutions to address the everyday business challenges, all of these seemingly difficult to achieve goals become significantly easier. This shift in the industry to becoming more transparent applies not only to ingredients and sourcing but also through publishing implementation of measures to achieve Net-Zero objectives, while also increasing quality and safety standards. A simple search for some of the world’s largest Food & Beverage corporations will provide a view into this increased transparency, with many having entire pages or websites worth of information on their Net-Zero objectives.

“Net-Zero refers to the balance between the amount of greenhouse gas produced and the amount removed from the atmosphere.”

National Grid

These initiatives have become increasingly important in the battle against climate change, though often highly politicized, with corporations in the United Kingdom and Europe currently leading the charge through their participation in setting national goals with the regards to the Paris Agreement. However, they aren’t the only ones as large multinational, U.S. based F&B corporations such as PepsiCo and Coca-Cola have been setting the Gold Standard for the industry in their race towards Net-Zero.

In January of 2021 PepsiCo announced plans to “more than double its science-based climate goal, targeting a reduction of absolute greenhouse gas (GHG) emissions  across its value chain by more than 40% by 2030. In addition, the company has pledged to achieve net-zero emissions by 2040, one decade earlier than called for in the Paris Agreement.”

Within their announcement, they detailed how they would achieve this goal, and the answer lies partially in technology, with an emphasis on “implementation and upgrading of environmentally sustainable manufacturing, warehousing, transportation and distribution sites,” and a corporate goal to “maximize efficiency in supply chain, while also adopting zero- and near-zero-emission technologies.”

PepsiCo is a behemoth in the industry with a holistic view and detailed strategy for achieving their ambitious international Net-Zero goals.

While the large players like PepsiCo and Coca-Cola may be leading the way, due to their significant global stage and highly publicized plans, other Food and Beverage manufacturers have certainly been and can continue to meaningfully contribute to international net-zero goals.

The UK has been making significant progress as they have a national goal of bringing all greenhouse gas emissions to net-zero by 2050. According to the Food and Drink Federation, the UK food supply chain is responsible for around 20% of UK greenhouse gas emissions. Inenco reports that, “a rate of around 3% annual reductions by the manufacturing sector is needed to meet the ambitious 2050 net-zero targets,” further illustrating that the food and beverage sector, which is the UK’s largest manufacturing sector, accounting for 15.6% of total manufacturing GVA, needs to lead the way.

As discussed in our previous article, the food and beverage industry face unique challenges in that margins are already razor thin, recovery from negative supply chain impacts from Covid-19 and the competition of a $6111.1 billion industry is staggering. All of these mounting pressures represent an opportunity for innovation and the implementation of innovative Artificial Intelligence technologies to the value chain. Artificial Intelligence, such as Maestro, presents a ready solution to tackle all of these industry pressures swiftly through process innovation that will result in value chain optimization with a host of benefits including increased resource efficiency, reduced waste and a whole lot more.

Focused entirely on maximizing clients’ profitability and sustainable growth, Elutions’ proprietary Enterprise AI platform, Maestro, delivers unprecedented benefits with certainty and at scale through autonomous and automated AI. Maestro’s neural network self-generates algorithms and implements directives without the need for human intervention, optimizing the entire value chain, and delivering benefits that continue to grow through a virtuous circle that sustains margin growth.

Maestro AI is proven to deliver transformational benefit for the F&B manufacturing industry allowing clients to achieve Net-Zero goals with increased speed to value. To learn more about Maestro AI and Elutions, contact us.

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January Series- Artificial Intelligence and the Oil & Gas Giants

The Oil & Gas industry is recognized as one of the largest valuation markets in the world and it is universally recognized for the reliance that the global markets hold on oil as a natural resource. Additionally, Oil & Gas corporations employee tens of thousands of individuals and often contribute significantly to their country’s GDP, resulting in increased political influence. Given their reliance as both a regional and market driver, it is no surprise that this industry is heavily investing in Artificial Intelligence to increase the value of their entire supply chain.

All equally Upstream Downstream Midstream What part of the industry can be most helped by intelligent enterprise? 65% 21% 10% 4% Which parts of the oil and gas value chain will be most affected by intelligent enterprise? (choose three) Asset integrity & maintenance Field development Geophysical Pipelines Drilling Refining Power generation Transportation (tankers & trucks) Construction Gas processing Product marketing Liquefaction Other Storage 69% 35% 32% 30% 28% 25% 21% 18% 13% 12% 5% 1%
Source: Oil & Gas IQ

Around 200 oil and gas professionals from around the globe took part in Oil & Gas IQ’s in-depth research into the intelligent enterprise landscape and the impact of AI as the next driver of change within the industry. Some interesting results above illustrate that a majority of these O&G professionals believe the industry will be helped by intelligent enterprise equally, upstream, midstream, and downstream. Additionally, a majority of respondents top choice for their number one value chain improvement with intelligent enterprise was asset integrity & maintenance.

This New Year, Solve the Unsolvable will be drilling into the world of Oil & Gas and how Artificial Intelligence will exponentially increase the value of this industry, especially in the areas industry professionals have identified as most important. In Q1 2021, we will be exploring how AI addresses the vulnerability of supply within the O&G ecosystem, including a deep dive into AI’s ability to eliminate unplanned maintenance and prevent failures at scale. A look at how the decreasing cost of Oil is driving corporations towards AI in order to increase profitability by re-evaluating their value chain operations. And finally, a view into the rapidly expanding US Shale market, which is uniquely poised to benefit from AI at the very early stages.

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Artificial Intelligence: A Green Chemistry Technology

Sustainability has been a buzzword for at least the last decade across all industries and even within people’s homes but it seems now, more than ever, it is actually becoming a leader in disruptive change for corporations all over the globe. We see this push in Chemistry with the increased focus on “Green Chemistry” which the Environmental Protection Agency (EPA) defines as “the design of chemical products and processes that reduce or eliminate the generation of hazardous substances.”

Green Chemistry represents a broad reach in the Chemical Industry to become more sustainable in many different facets of the word. The EPA states that corporations that create technology which, “reduces or eliminates the hazardous chemicals used to clean up environmental contaminants” are creating green chemistry technology. Per this definition, Artificial Intelligence, when applied to Chemical Manufacturing Process to reduce environmental contaminants or when used to develop materials in a less hazardous way, and many more applications, can and would be considered green chemistry technology.

ne 12 Principiu of o GREEN CHEMISTRY • Green chemistry is an approach to chemistry that aims to maximize efficiency and minimize hazardous effects on human health and the environment. While no reaction can be perfectly •green', the overall negative impact Of chemistry research and the chemical industry can be reduced by implementing the 12 Principles Of Green Chemistry wherever possible. l. WASTE PREVENTION Prioritize the prevention Of waste, rather than cleaning up and treating waste after it has been created. Plan ahead to minimize waste at every Step. 2. ATOM ECONOMY Reduce waste at the molecular level by maximizing the number Of atoms from all reagents that are incorporated into the final product. Use atom econonny to evaluate reaction efficiency. 3. LESS HAZARDOUS CHEMICAL SYNTHESIS Design chemical reactions and synthetic routes to be as safe as possible. Consider the hazards of all substances handled during the reaction, including waste. 4. DESIGNING SAFER CHEMICALS Minimize toxicity directly by molecular design. Predict and evaluate aspects such as physical properties, toxicity, and environmental fate throughout the design process. 5. SAFER SOLVENTS AUXILIARIES Choose the safest solvent available for any given step. Minimize the total amount Of solvents and auxiliary substances used, as these make up a large percentage Of the total waste created. 6. DESIGN FOR ENERGY EFFICIENCY Choose the least energy-intensive chemical route. Avoid heating and cooling, as well as pressurized and vacuum conditions (i.e. ambient temperature & pressure are optimal). 7. USE OF RENEWABLE FEEDSTOCKS Use chemicals which are made from renewable (i.e. plant-based) sources, rather than other, equivalent chemicals originating from petrochemical sources. 8. REDUCE DERIVATIVES Minimize the use Of temporary derivatives such as protecting groups. Avoid derivatives to reduce reaction steps, resources required, and waste created. 9. CATALYSIS Use catalytic instead Of stoichiometric reagents in reactions. Choose catalysts to help increase selectivity, minimize waste, and reduce reaction times and energy demands. 10. DESIGN FOR DEGRADATION Design chemicals that degrade and can be discarded easily. Ensure that both chemicals and their degradation products are not toxic, bioaccumulative, or environmentally persistent. Il. REAL-TIME POLLUTION PREVENTION Monitor chemical reactions in real-time as they occur to prevent the formation and release Of any potentially hazardous and polluting substances. 12. SAFER CHEMISTRY FOR ACCIDENT PREVENTION Choose and develop chemical procedures that are safer and Inherently minimize the risk Of accidents. Know the possible risks and assess them beforehand. Ci O COMPOUND INTEREST 2015; WWW.COMPOUNDCHEM.COM Shared under a CC Attribution-NonCommercial-NoDerivatives licence. BY NC ND
source: www.compoundchem.com

Dr. Paul Anastas, known as the “Father of Green Chemistry” and the Director of Yale’s Center for Green Chemistry & Green Engineering, has shed even further light on sustainable chemistry sharing his ideas that not only is Green Chemistry about aligning environmental and health goals but also the consideration that “Green” must extend to economic goals through new inventive and innovative change.

Dr. Yuan Yao, a rising star in the industry and a Yale Professor, has worked alongside Dr. Anastas to conduct investigative research that illustrates, “…how emerging technologies and industrial development will affect the environment,” and she also uses, “interdisciplinary approaches in industrial ecology, sustainable engineering, and machine learning to develop systems analysis tools to support engineering and policy decisions towards sustainability.”

It is Dr. Yao’s belief that, “artificial intelligence shows great potential in reducing the energy consumption and environmental footprints for the chemical industry.” And the team at Solve The Unsolvable and Elutions have to agree with her, as our lengthy experience in chemicals and beyond prove this statement to be true. 

Artificial Intelligence, and Elutions’ Maestro Platform specifically, can certainly be considered innovative and a large contributor to sustainable chemical manufacturing. Our team works tirelessly to solve previously unsolvable business quandaries in the Chemical Industry and beyond to create more sustainable business processes and practices. Through the bespoke application of Maestro AI across the entirety of the chemical manufacturing process, from procurement all the way through to the sale of the product, enterprise efficiency is taken to a new level.

Not only does Maestro cover many of the 12 Principles of Green Chemistry such as waste prevention & energy efficiency but it goes far beyond to incorporate Dr. Anastas’ ideals of taking into account economic goals, through significant operating margin increases and constant innovation within our Neural Network. Maestro maximizes benefits with continuously increasing speed, scale, and impact.

To learn more about Maestro, please contact us and to read more about our work in chemicals, and beyond, please subscribe below.

Up Next for NCW: Digitization and Chemical Manufacturing

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National Chemistry Week Celebration!

Each year in the United States, since the late 1980s, the American Chemical Society (ACS) has designated a week, National Chemistry Week (NCW), to celebrate and promote to the public the positive changes in the Chemical Industry. This year’s NCW theme is “Sticking with Chemistry” with a focus on Glues and Adhesives, something that touches all of our lives, almost daily and especially the lives of children. While the ACS predominantly focuses on educating elementary and secondary school children, we would like to share our thought leadership with businesses around the globe.

As a company with several partnerships within the Chemical Industry, including a membership in the Chemicals Industry Association in the United Kingdom, Elutions is excited to share the positive changes we, and Artificial Intelligence in general, have made through Chemical Themed articles celebrating this year’s National Chemistry Week from October 18th through October 24th.

Please check out our upcoming articles on Monday 10/19, Wednesday 10/21, and Friday 10/23 about the positive changes being made, specifically in the Chemical Manufacturing Industry, through Artificial Intelligence and our AI platform, Maestro.

To learn more about Maestro, please contact us.

Up Next for NCW: Digitization and Chemical Manufacturing

Stay up-to-date on this series and all of our industry disrupting insights!

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Virtual CogX: The Festival of AI & Breakthrough Technology

Elutions is proud to announce their Lead Partnership of The CogX Global Leadership Summit and Festival of AI & Breakthrough Technology, June 8th- June 10th. In a world that is constantly in flux to adapt to impacts of COVID-19, CogX made the difficult decision to virtualize their event. We fully align with this decision as they themselves said,

“There are important, and in some cases urgent, topics to discuss: both the immediate challenges presented by COVID-19, and to play our part in helping restart the economy by connecting, collaborating and supporting each other.”

Relevant, now more than ever, is CogX’s 2020 Event Theme- How Do we Get the Next 10 years Right? Outlined below are the ways in which the conference aims to address this massive question:

– Move the conversation forward with concrete actions

– Reframe the climate emergency as the biggest economic opportunity in the last 200 years

–Increase understanding of the current Covid-19 pandemic and champion innovative solutions

The global pandemic has allowed many of us, corporations and individuals, to pause and re-evaluate what the next ten years will look like. It is clear now that the businesses that successfully and swiftly adopt to automated, autonomous applications of AI and rethink their business models will be the ones realizing a competitive advantage.

We will be hosting a virtual expo booth across the three days, June 8th through June 10th, where attendees can reach out to our team to learn more. We will also be hosting virtual lunch and learns, happy hours, and coffee chats. Our Managing Director of EMEA, Jamie Devlin, will also be a featured speaker on Industry 4.0 and sustainable supply chain, Monday, June 8th, 5pm BST (12pm EST).

For a limited time, we are offering our readers, interested in attending our speaking events, the chance to receive a Gold Pass, free of charge. Please click here and provide your full name, title at your company, email address and phone number to receive a Gold Pass.

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College and University Campuses can Combat COVID-19

It’s graduation season around the world and for what seems like the first time, graduation will not commence per usual. The celebratory hustle and bustle of college campuses at this time of year is now replaced with empty classrooms, haunted hallways and desperate hopes that students will return in the Fall. The truth is, nobody knows what will happen in the Fall semester, but students aren’t the only ones feeling the immediate impacts of campus closures. Colleges and Universities are now scrambling to address not only the concerns of parents, students, and staff but also the significant impacts on endowments, revenues and their budgets going forward.

An Inside Higher Ed survey of 172 campus leaders shows that the number one concern remains bringing the students back to campus safely and continuing their high standards for education off campus. However, the financial focus is right up there, “more presidents citing a desire for financial health and operational planning support (60 percent) than for anything else.” Artificial Intelligence can address operational concerns while freeing up financial resources for other concerns such as faculty training and instructional technology.

Source: Inside Higher Ed

While revenues are experiencing immediate impact, the need to protect buildings and assets, ensure environmental compliance is met, and reduce building baseloads becomes more critical as staff and services are less present. After all, students need a campus to return to. Artificial Intelligence, and Maestro specifically, is primed to not only address these impacts in the immediate term but provide long-term stability and digital transformation.

At an operational level, buildings have been closed but the need to maintain them to prevent asset degradation and compliance requirements still need to be met. With fewer people onsite to identify and manage issues and IT stretched with online learning, now more than ever AI and autonomous or remote adoption of solutions need to be applied. At this point, it is likely that there are already significant maintenance backlogs, which AI can address and mitigate future negative impacts of.

The short-term, mid-term and long-term impacts can all be addressed through Maestro artificial intelligence in the following ways:

Short Term: Reduce costs, ensure compliance and protect assets through improved approach to managing assets with limited onsite staff. Optimize baseloads. Identify and prioritize critical failures. Iron out inconsistencies in data. Move to PPM.

Mid Term: Significant cost savings in resource efficiency, maintenance, increase asset life use, reduced capital expenditure.

Long Term: Enhanced scenario modelling for space optimization and asset acquisition ROI assessments.

Benefits like this can be achieved through Maestro’s artificial intelligence and neural network computing capabilities to target significant energy and maintenance cost reduction opportunities through automated, no-cost measures across the campus, eliminating the need for direct human interaction with the on campus assets. A run-rate to deliver a benefit of >$20m annually could easily be achieved in as little as 60 days through a rapid deployment of the technology and the prioritization of the highest energy cost consuming facilities.

In an effort to focus on creating a stable environment for students to come back to, Higher Education Institutions must turn to AI as a remedy for immediate negative financial and operational impacts caused by COVID-19. To learn more about how AI can turn your business operations around, stay tuned for our COVID-19 & AI series or contact our team today to learn more.

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AI & COVID-19: Stabilize & Survive

In the midst of the COVID-19 pandemic, why are corporations accelerating rather than delaying their digital transformation initiatives? The pandemic’s unprecedented impact on demand, workforce, supply chain, short-term costs and liquidity has forced corporations to take immediate, strategic action to maintain operations. In exploring their means of stabilization and survival, corporations found that Artificial Intelligence is uniquely positioned to ensure business continuity in the short-term, with its proven value in improving employee safety & security, short-term costs and liquidity.

While no industry has proven immune to the pandemic, the depth and breadth of its disruption in the manufacturing vertical clearly demonstrates why corporations have adopted transformational technologies over traditional solutions to beat COVID-19. Manufacturers have felt the acute pressure of COVID-19 in their plants and across their value chains.

  • Demand: Sharp declines in demand across non-essential product segments have disrupted each step of the value chain, driving significant earnings adjustments; essential goods producers are struggling to continue operations with heightened risk, and to satiate demand with unprecedented operating and supply chain limitations.
  • Supply Chain: Despite the geographic diversity of supplier networks, sudden overseas supplier shutdowns and domestic fulfillment delays have disrupted if not halted downstream activity, depleting on-hand inventory, prompting a rapid search for market alternatives, and driving material and part shortages, price increases, and an expected spike in upstream transportation costs as restrictions lift.
  • Workforce: Rapid adoption of new distancing protocols, shift structures and offsite resourcing arrangements have ensured employee safety & security, but constrained operating efficiency, quality, throughput and yield; deferred critical asset maintenance and replacement have increased downtime risk and may increase mid-term CAPEX obligations.
  • Short-Term Costs: Essential and non-essential product manufacturers have made significant adjustments to minimize variable costs, maintain business operations, and operate in an environment of significant macroeconomic and trade policy uncertainty, including layoffs, furloughs and temporary plant closures.
  • Liquidity: With strong macroeconomic headwinds, demand and supply side disruption, and constrained operational agility, liquidity is a principal concern of manufacturers that will not be alleviated at the moment restrictions are lifted, but gradually as the supply chain and broader economy rebound.

How is Artificial Intelligence empowering corporations with substantial value chain disruption to act fast and weather the storm?

Elutions’ highly-automated and autonomous Artificial Intelligence solution, Maestro, leverages historical data, deploys rapidly and delivers immediate improvements in safety & security, short-term costs and liquidity. The following Artificial Intelligence use cases are paramount to ensuring business continuity in manufacturing.

  • Remote Operability, Operational Automation & BEP Adherence: By enabling remote asset and process control, visualization and planning, and automated system-driven asset and process optimization, corporations ensure operational continuity, resilience and efficiency, improving employee safety & security, reducing labor requirements and operating costs, and increasing cash-on-hand.
  • In-Line Quality Assurance & Scrap Reduction: By enabling automated quality prediction and dynamic operating parameter adjustment at each stage of production, manufacturers autonomously ensure end-product quality, minimize scrap and rework, and optimize the Unit Cost of Production as conditions change, improving operating margins, yield (revenue), and liquidity through minimized waste.
  • Dynamic Downtime Prevention & Predictive Preventative Maintenance: By enabling dynamic, system-driven alternate control sequencing in the event of a sensor, asset or process failure, corporations autonomously avoid unplanned downtime, associated repair and replacement costs, and foregone revenue. With system-driven Predictive Preventative Maintenance and automated Work Order creation, corporations minimize downtime and production risk, extend asset use life, generate significant savings through right-time, right-size maintenance, and improve safety & security through truck-roll consolidation.
  • Market, Demand & Capacity Driven Procurement & Inventory Management: By continuously predicting raw material costs, sales and capacity alongside the live environment, and enabling automated procurement and IM directives, corporations optimize operating productivity, inventory levels, and the margin value of Inventory on-hand. Similarly, by continuously predicting replacement part costs, process demand alongside forecasted utilization, and automating replacement part purchasing, corporations optimize part inventory levels, reduce short-term costs and improve liquidity.

Beyond short-term survival, corporations have placed their bets on Artificial Intelligence to thrive in the mid-to-long-term. Stay tuned for more market intelligence on how AI is helping corporations build resilience and optimize operations.

Up Next for NCW: Digitization and Chemical Manufacturing

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Preparing for Landing: AI, Airports & COVID-19

An industry that felt a near immediate and drastic impact from COVID-19 was the air-travel industry. With the COVID-19 measures and bans, a large part of air traffic, mostly passenger but also cargo, has come to a near standstill across the globe. Air traffic has historically been cyclical, closely following the regional and global economic growth metrics, and it had experienced unexpected downturns during or after tragic events like 9/11. However, it has never been hit by an incident of this magnitude that led to reports by TSA of less than 1% of the amount of travelers going through airport security year over year from this time in 2019 to now.

Take Atlanta’s Hartsfield-Jackson a once bustling airport and one of the world’s largest and busiest hubs has now reported massive losses. According to the airport’s general manager, John Selden, “Revenue is probably down, off the top of my head, 50 to 60%,” he also added, “we usually have 2,600 flights a day here, fully loaded. In other words, almost no seats available. Right now, we’re down to 1,200 flights and they’re mostly empty.” The airport is down 85% in passengers.

While there is no clear picture on when air traffic will recover, looking at the TSA reports there is a clear increase in travel during the month of May thus far, at least in the US. Domestic markets are expected to be opened first, following the example in China. However, consumer confidence and regaining the trust of travelers will be integral to the timing and speed of industry recovery.

According an IATA-commissioned survey, 40% of passengers say they will wait 6 months or more before traveling. The recovery will also depend on the financial outlook as a prolonged global recession will dampen demand for air traffic further.

The uncertainty surrounding travel is leaving many leaders to wonder,

“How can we ever recover from this?” 

The answer lies in the application of Artificial Intelligence.

Artificial Intelligence-led initiatives will provide a helpful remedy to the negative impacts of the COVID-19-led disruption and will also inform post-COVID-19 operating models as they are developed and tested. As for many other industries, it is imperative to recovery for airports to fast-track AI-led initiatives in these times of increased operational uncertainty and unforeseen structural changes.

In the short to medium term, AI will help airports minimize their operational costs by increasing resource efficiency according to operational demand and reducing maintenance costs through predictive preventative maintenance, and maintain, possibly even enhance, their standards of operations with a reduced workforce through its autonomous application. In turn, greater flexibility will be provided to airports which had been forced to suspend terminal and runway capacity and reduce workforce as an immediate response to the loss of air traffic, particularly as some of the travel demand returns over the next few months.

In the medium to long term, AI will inform future operating models as airports will develop and test new ways to run every bit of their operations from car parks to passenger gates. Insights gained by AI will add a strategic value to airports as they plan for their future.

Businesses that successfully and swiftly adopt to automated, autonomous applications of AI and rethink their business models will be the ones realizing a competitive advantage once we return to normalcy. Contact our team today to harness the power of Elutions’ Artificial Intelligence Solutions.

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AI & COVID-19

Throughout modern history, several infectious diseases have spread with sufficient speed, scale and severity to be considered pandemics. Malaria, Smallpox, H1N1, and HIV/AIDS, which remains active, made the list. COVID-19, however, is in a league of its own. The last pandemic of comparable economic impact, if not on human life, was the Spanish Flu, which directly followed WWI and wrought havoc in a significantly less interconnected world than the one in which we live today.

The Global Impacts of COVID-19 have already been unprecedented. “Stay-at-home,” “social-distancing” and travel and trade restrictions imposed to protect public health have had devastating impacts on the global economy, supply chain and employment. How and when this pandemic will end remains unclear. What is certain is that businesses now face an existential threat, and their leaders must take immediate action to set and execute strategies to weather the storm and ensure they are prepared for future economic, operational or human crisis.

In a time when “non-essential” businesses have been forced to shutter operations or shift to remote collaboration, and “essential” businesses face unparalleled demand alongside novel operational and supply chain challenges, how can manufacturers, O&G companies, airports, utilities, universities and other major businesses survive?

If they adapt quickly, can they thrive?

The answer to this question for industry lies in the adoption of end-end Artificial Intelligence.

Over the next few weeks, we will dive into the major business impacts of COVID-19 and how Elutions‘ Artificial Intelligence platform, Maestro, is addressing them across multiple verticals.  We strongly believe that businesses that successfully and swiftly adopt automated, autonomous applications of AI and rethink their business models will be the ones realizing a competitive advantage once we return to a “new normal”.

Inspired by industrial trends a multitude of sources, reports by McKinsey and many others, Elutions’ AI & COVID-19 Series will specifically address the themes of Survival, Optimization, and Transformation. 

Survival: Artificial Intelligence applied immediately to stabilize business operations.

Optimization: Artificial Intelligence’s intermediary impacts, growing and preparing for a “new normal.”

Transformation: Artificial Intelligence’s long-term impacts in a post-pandemic landscape.

Check back in with us weekly for new content on how to address the business impacts of COVID-19 through the strategic application of end-end Artificial Intelligence.

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Why In-House Artificial Intelligence Projects Fail

Companies all over the world, from giant corporations to start-ups, are keen to cash in on the vast value of Artificial Intelligence. With an intent to capture as much of that value as possible, many spend millions on in-house AI solution development rather than outsourcing to address their most critical business challenges. In a world where there’s a feasible DIY solution for almost everything, Artificial Intelligence is most often the outlier. The complexity and cost of AI solution development demands experience to reduce financial risk and ensure speed to benefit, especially in highly competitive sectors.

Think of your business as a human body, and your business challenges as illnesses of varying severity. Some challenges, like some illnesses, are treatable with over the counter medications, while others require a visit to the doctor, prescriptions, long-term treatment or intensive care. If you had an illness that required extensive medical attention, you wouldn’t hesitate to seek out the best medical team for treatment. Should you treat your business any differently?

In deciding whether to go in-house or outsource, it is important to consider how a strategic AI implementation will impact your business. If it’s done right, it will reduce costs, increase revenue and enhance competitive advantage. If it’s done wrong, to what extent is your business at risk?

Financial opportunity from AI abounds across sectors (see the figure below), and there is both margin opportunity and market share on the table for the businesses that harness AI to tackle their strategic challenges first. In other words, getting your AI implementation done fast and right matters, and you must weigh your decision to go in-house or outsource accordingly.

Artificial intelligence (Al) has the potential to create value across sectors. Al impact, $ billion 700 500 400 Healthcare systems and services Public and social sectors 300 Advanced electronics/ semiconductors Retail Transport and logistics Travel Consumer packaged goods Automotive and assembly Banking Basic materials Insurance Media and entertainment High tech O Oil and gas 100 20 Telecommunications Pharmaceuticals and medical products 30 Chemicals Agriculture Aerospace and defense 40 50 60 McKinsey&Company Share of Al impact in total impact derived from analytics, % Source: McKinsey Global Institute analysis

With competitive advantage on the line and the clock ticking, corporations place their bets on whether to navigate the AI journey alone or with partners. Instinctively, they are hesitant to collaborate, tantalized by the prospect of minimizing solution costs, while building their own innovative capacity and owning the resulting IP outright.

Logically, they then look to market outcomes and learn why in-house AI solution development efforts fail more often than not, even in the Fortune100 and at tech companies.

Without experience developing and delivering AI solutions, many corporations fail understand the costs, resources, processes, stakeholders, and even the objectives involved from the onset. As a result, in-house projects often lack a clear and viable design and delivery strategy, roadmap and KPIs, dramatically reducing the speed to benefit if not inhibiting benefit delivery altogether. Program costs and timelines become a driving force for failure. With little transparency into which aspects of the solution will drive the most value, there is no clear way to prioritize spending. Costs either spiral out of control, or corners are consecutively cut in design, development, testing and delivery, resulting in piecemeal solutions that impair data quality, promote bias and diminish solution accuracy, functionality, utility and outcomes.

More often than not, successful AI adopters partner with proven providers on a combination of off-the-shelf solution tailoring, ground-up solution design and solution delivery. How do they decide to partner rather than go it alone?

First, they recognize the competitive imperative for AI—the opportunity cost of following rather than leading in their market—along with the direct costs of failure, and their lack of in-house knowledge and experience with AI solution design and delivery. Second, they find a provider with a successful track record in similar or analogous environments. Third, they develop trust with that provider by laying the groundwork for a happy marriage in contracting. Then they see it through. From the leadership level-down, they commit to the partnership and collaborate from end-to-end to ensure project success.

Strategic AI implementations are broad in scope, capturing data and impacting activities across corporate ecosystems. This complexity is readily apparent in industry, where AI not only provides data-driven direction for decision-making at every step of the value chain and in every organizational department, but directly informs control and automation strategies in production, testing, packaging, distribution and even purchasing.

In recognition of the immense value and complexity of AI in industry, and the competitive need for speed in adoption, the World Economic Forum, in collaboration with McKinsey & Company, has published a toolkit of “practical recommendations” for industrials to accelerate their AI journey at scale. Appearing in The Next Economic Growth Engine Scaling Fourth Industrial Revolution Technologies in Production, this toolkit advocates the adoption of proven AI solutions and related technologies through a partnership and acquisition approach rather than in-house development.

Figure 6: Industry toolkit for accelerating adoption of technology Value delivery engine Intelligence • Predictive maintenance • Machine learning-supported, root-cause problem-solving for quality claims Connectivity Augmented reality-guided assembly operations Real-time IOT-based performance management Flexible automation • Robots to automate challenging tasks • Real-time product release 39 high-impact digital applications ready for deployment Scale-up engine Mobilize Mobilize the Organization Strategize Set the vision and the value to capture Innovate Spark innovation by demonstrating the value at stake Scale up Capture full value & Company, Fourth in With the World

With more and more data available for exploit across industries, the opportunities for its monetization through AI are greater and increasingly complex. So too is the risk of getting your implementation wrong.

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