Digital Transformation, Artificial Intelligence and the Chemical Industry

In the previous articles in this series, we discussed the importance of the Chemical Industry to the global economy and how that industry is poised to benefit tremendously from digitization. Digitization is a vast concept, it encompasses everything from advanced analytics and process controls through to Artificial Intelligence and full automation. Although many experts agree that digitization is critical for the future of the industry, what exactly that means in a business application remains to be seen.

STEPS TO BRING 
DIGITAL TRANSFORMATION 
IN THE CHEMICAL INDUSTRY 
ORGANIZATION 
AND TECHNOLOGY 
DIGITALIZE 
THE ENTERPRISE 
REGULATION 
ECOSYSTEM 
COLLABORATION 
CYBER SECURITY 
WORKFORCE 
AUTOMATION 
AND ROBOTICS 
INDUSTRIAL 10T 
CULTURAL 
CHANGE 
NEW BUSINESS 
MODEL 
BRING THE WORKFROCE 
INTO THE DIGITAL AGE 
RIGHT DIGITAL 
STRATEGY 
CHEMICAL 
SALES IN 2016 
€3.5 trillion 
NIO million 
PEOPLE EMPLOYED 
IN THE INDUSTRY 
USING ADVANCED 
TECHNOLOGY 
CONTRIBUTION OF 
THE INDUSTRY TO 
GLOBAL GDP 
€6.9 
trillion 
RECAST CHEMICALS 
SALES IN 2030 
THE IMPORTANCE 
INDUSTRY 
-100.000 
CHEMICALS ON THE 
ENSURE 
CYBERSECURITY 
ENSURE REGOLATORY & 
HARMONIZE POLICIES 
CHANGING 
THE MINDSET 
STRENGTHENING 
KEY AREAS 
ARTIFICIAL 
INTELLIGENCE 
CLOUD 
MOBILITY 
CONVERGENCE AND DEVICES 
PLATFORMS AND 
APPLICATIONS 
BIG DATA 
ANALYTICS 
90% 
EVERYDAY PRODCUTS 
CONTAINING CHEMICALS 
O PINPOOLS 
Wm.".pinpools.com 
MARKET TODAY 
CONTINU S 
DEVELOPMENT 
MANAGEMENT 
o 
PROFITABLE 
OPERATIONS 
INNOVATION 
PROCESS 
OPTIMIZATION 
BETTER SUPPLY CHAIN 
MANAGEMENT 
INCREASE 
PRODUCTIVITY 
SOURCE: WOLRo Econowc FORUM • 01GlT,u TRANSFORMATION 'NIATr.'E
Source: Pinpools

Industrial digital transformation represents a host of possibilities, whether it’s a reference to digital technologies applied in various levels of the process, to the entire process or even to the entire estate. For the purpose of this article, at a process level, Chemical Manufacturing and Artificial Intelligence will be the main focus of digitization in chemicals. Transformational benefits such as increased margins, reduced downtime, sustainable business practices, and more are all achievable in chemical manufacturing through the application of Maestro Artificial Intelligence.

For many corporations it may be tempting to apply digital technologies such as Artificial Intelligence, at a plant level or in an ad hoc basis and while benefits can certainly be achieved this way, in order to be truly transformative, from our years of experience, estate wide application is a necessity. Estate wide application allows for a full picture of the process rather than a point in time, isolated view of the equipment. The estate wide view gives way to a true understanding of how upstream and downstream processes impact the entirety of production.

The adoption of Artificial Intelligence across the entire estate is pivotal to the growth strategy of industrial chemical manufacturing and to their ability to combat digital-led disruption in end markets.


Long term consequences from the adoption of digital in other industries is being predicted to cause a large ripple effect in chemicals. The ripple effects can be positive or negative, take the following example: Digital technologies applied to the automotive value chain will have tremendous impact on the demand for production of chemical coatings as the dawn of driverless cars is set to increase safety on the roads and decrease the needs for chemical coatings. While a world filled with driverless cars may seem like a distant future, Chemical Manufacturers that produce these coatings need to begin planning for this disruption by applying digital now in order to survive in the future.

We have all learned many lessons about the uncertainty of the future, especially due to the impacts of the global COVID-19 pandemic, which manufacturers have suffered extensively from. Where have manufacturers turned in order to correct the course? Digitization. An internal research study revealed that the largest drivers for digitization in the chemicals industry are workforce, changes in utilities/ energy costs, COVID-19 related changes, growth strategy and global industry pressures.

Source: Internal Research

Financial incentive alone, derived from increased production, decreased downtime etc., is a significant reason to go digital. Additional benefits relating to sustainability such as reduced energy consumption and hazardous waste are also key drivers. Reduced research and development cycles are another fantastic benefit that comes from digitization.

The above drivers are the “why” that is causing Chemical Manufacturers to adopt digital technologies at increased rates. But how can they drive benefit, adopt solutions quickly and do it all at scale? 

The most important decision in adopting Artificial Intelligence and digitizing is choosing the partner that will transform business operations.


A true partner, like Elutions, will work with the business to establish clear targets, quantify the benefit, develop a governance plan, create a bespoke solution for targeted needs, prioritize speed to benefit and above all remain committed to future growth and surpassing designated targets and goals. Digitization in chemical manufacturing is not a “one size fits all.” Businesses deserve a partner that understands that and is experienced in working together to create the perfect fit.

To learn more about specific case studies of Maestro Artificial Intelligence applied, please contact us.


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Artificial Intelligence and the Chemical Industry’s Rebound from COVID-19

It should come as no surprise that the Chemical Manufacturing Industry, like all industries, has experienced quite a shake up this year due to the COVID-19 pandemic. Global supply chain disruption, erratic spikes and lulls in demand, operational constraints and the nature of on-site jobs are just a few of many obstacles that the Chemicals industry faced as a result of the pandemic.

Let’s consider some chemical industry statistics that frame the impacts of these constraints on the global economy…


According to the US Bureau of Labor Statistics from data in September 2020, Chemical Manufacturing companies employ roughly 838,000 people in the United States alone, of that 838k roughly 524,000 are production and nonsupervisory employees.

The below figures are according to statista.com: 

In 2019, the Chemical Industry represented a total worldwide revenue of roughly 3.94 trillion U.S. dollars, with China controlling a 35.8% share of the revenue.

The leading Global Manufacturer of Chemicals, based on a revenue of approximately 65.3 billion U.S. dollars, was German chemical company, BASF. They were also the leaders in the category of global employment with approximately 118,280 employees.

In the United Kingdom the chemical and pharmaceuticals industry represent the second largest industry and a significantly important part of the national economy.


Based on this small sample of statistics alone, it is very clear to see that the Chemical Manufacturing Industry represents a significant part of our global economy. The good news is that as we learn more about the virus and find creative strategies to combat it, including artificial intelligence applied in various ways, we are already starting to see the Global Chemical Production rebounding from some pretty significant losses.


Percent change in chemical production due to COVID-19 worldwide 
between January 2020 and August 2020, by region 
GIObal 
Africa & 
Middle 
East 
Chile 
Latin 
America 
Mexico 
North 
America 
India 
China 
Asia. 
Pacific 
Former 
Soviet 
union 
Belgium 
Italy 
France 
Europe 
January 
2020 to 
Februa ry 
-2.1% 
0.1% 
2.3% 
-0.4% 
-0.1% 
-6.4% 
-3.7% 
-0.9% 
0.5% 
February 
2020 to 
March 
-3.3% 
0.2% 
-2.5% 
-1.1% 
-7.2% 
-8.3% 
-5.4% 
2% 
-0.8% 
-2.1% 
0.2% 
March 
2020 to 
April 
0.1% 
-8% 
-3.4% 
-2.9% 
-2.6% 
-15.9% 
1% 
-0.4% 
-0.1% 
-5% 
-4.2% 
-2.3% 
April 
2020 to 
May 
-0.5% 
-0.9% 
-10.2% 
-4.9% 
-6.5% 
-2.3% 
-13.7% 
4.8% 
1% 
-3.3% 
-3.9% 
-3.1% 
May 
2020 to 
June 
2020 
1.6% 
-1.2% 
-6.7% 
-3.2% 
-1.9% 
1.1% 
6.5% 
3.3% 
3.7% 
0.9% 
0.2% 
June 
2020 to L 
July 
1.7% 
0.3% 
-1.9% 
0.5% 
-1.1% 
1% 
17.6% 
2.1% 
1.7% 
1.9% 
2.8% 
5% 
3.2% 
3% 
July 2020 
August • 
2020 
2.7% 
2.9% 
4% 
0.9% 
10.3% 
3.3% 
2.9% 
1.3% 
2.6% 
4.9% 
1.7% 
3.6%
Source: Statista

Global production is rebounding slowly, but surely, with a 2.7% uptick in production from July of 2020 to August of 2020 with the most significant increase coming from India after a pretty difficult downturn due to the COVID-19 pandemic. The rebound in this industry is pivotal to the health of our global economy, as illustrated by the statistics above which represent how important chemical manufacturing is.

What steps have the Chemical Manufacturers taken in order to begin rebounding quickly and contributing to our global economy?


Many Chemical Manufacturers have turned to Artificial Intelligence and Digitization in order to combat challenges presented by COVID-19 whether they are applying these technologies to part of their process or to their entire estate.

Let’s take the international race to find a vaccine as an example. Many corporations have worked together to use Artificial Intelligence to rapidly increase the ability to find a treatment. Dan Drapeau, Head of Technology at Blue Fountain Media, has posited that Artificial Intelligence, when applied in the capacity of finding a vaccine, has become “a necessity right now, because we’re in the middle of a global pandemic, and it’s vital for us to figure out a solution or vaccine therapy as soon as possible.

Mefuparib 
PARPI 
SARS-cov-2 
Toremifene 
Viral RNA 
NSP14 
RNA-dependent 
RNA polymerase 
Dexamethasone 
NR3C1 
Remdesivir 
AAKI 
Melatonin 
MTNRIA 
Baricitinib
Source: The Lancet
AI algorithms can be used for drug repurposing, which is a rapid and cost-effective way to discover new therapy options for emerging diseases.

Artificial Intelligence is a massive disruptor in the vaccination process in regards to reduction of time consumed by molecular analysis and how the molecules should be used in chemical binding to target the disease. In short, humans can’t possibly conduct analysis on the billions of different molecules as it would take far too much time that our global population just doesn’t have. AI has been able to automate this process for the pharmaceutical industry to increase capacity, help predict which drugs would most likely be successful and also decrease the amount of financial resources spent on clinical trials that might ultimately fail.

But Artificial Intelligence’s reach in the chemical industry only begins here and, as a result of the pandemic, it truly has become a necessity for corporations to survive and even thrive in the current environment.

Chemical manufacturers, as well as other industries, all over the world are partnering with Elutions in order harness the power of Maestro’s Artificial intelligence to combat the disruption that COVID-19 has created. Maestro, when applied to the chemical manufacturing process at an estate-wide level, has the ability to transform operations.

To learn more about Digitization and Maestro Artificial Intelligence, stay tuned for Friday’s (Oct. 23) article on Digitization and Quantifying the Impacts of Artificial Intelligence. Also, please read previous articles regarding our work using Artificial Intelligence to combat COVID-19.


Up Next for NCW: Digitization and Chemical Manufacturing


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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.

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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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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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.

Can your business afford the DIY approach?


Challenge us to solve your unsolvable business quandaries.


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