By The Valuentum Team
International Business Machines Corporation (NYSE:IBM) has become a fundamentally different business in the past few years, one focused on providing hybrid cloud computing offerings. The company is a stellar free cash flow generator which enables IBM to reward investors via generous dividend increases, with shares of IBM yielding ~5.1% as of this writing. Substantial near-term headwinds remain, largely due to the various exogenous shocks seen of late (such as major inflationary pressures, rising interest rates, supply chain hurdles, and raging geopolitical tensions), though IBM is still worth considering as a high-yielding income generation idea.
IBM solves business problems via integrated hardware/software solutions that leverage IT and its knowledge of business processes. Its solutions help reduce a client's costs or enable new capabilities that generate revenue. The company was founded in 1924 and is headquartered in New York.
Back in 2019, IBM bought Red Hat (a top provider of open source cloud software) through a ~$34 billion deal which made IBM a contending hybrid cloud provider. IBM is looking to seize what it describes as a ~$1 trillion hybrid cloud opportunity, and recent growth in this area has been encouraging. IBM's revamped management team is working hard to turn things around after the company made various blunders during the 2010s decade. Its current Chairman and CEO, Arvind Krishna, has done a solid job righting the ship at IBM since taking on the top role in 2020.
In November 2021, IBM spun off its legacy business tax-free to shareholders as a new publicly traded entity, Kyndryl Holdings, Inc. (KD). Initially, IBM retained a 19.9% stake in Kyndryl though the firm intends to exit that position within 12 months of the spinoff.
On July 18, IBM reported earnings for the second quarter of 2022 that beat both consensus top- and bottom-line estimates. Its GAAP revenues rose by 9% year-over-year to hit $15.5 billion with strong growth at its Red Hat, various consulting services, and hybrid infrastructure offerings being key here. When removing foreign currency headwinds arising from the strong US dollar seen of late from the picture, IBM's non-GAAP constant currency revenues were up 16% year-over-year last quarter. IBM's portfolio optimization efforts are having a very powerful impact on its financial performance.
The firm's GAAP gross margin fell by ~185 basis points year-over-year last quarter, falling down to 55.4%. However, economies of scale helped drive its GAAP income from continuing operations up by 81% year-over-year in the second quarter, rising to $1.5 billion. There is some noise here due to the separation of IBM's legacy businesses (via the spinoff of Kyndryl) from its core operations. Keeping that noise in mind, IBM's underlying operations have performed quite well of late.
During its second quarter earnings call, IBM's management team noted the firm now forecasted that its full-year free cash flows would come in near $10.0 billion in 2022, at the low end of its previous forecast. IBM generated $3.6 billion in free cash flow (defined as net operating cash flow less 'payments for property, plant, and equipment' and 'investment in software') while spending $3.0 billion covering its dividend obligations during the first half of 2022. Its modest share repurchases during this period were related to tax withholding purposes as the new IBM is focused on retaining cash to invest in the business. We appreciate that IBM's dividend obligations remain well-covered by its traditional free cash flows.
The company exited June 2022 with a net debt load of $42.8 billion (inclusive of short-term debt, exclusive of restricted cash). One of the biggest risks to IBM's dividend is its large net debt load. IBM had $7.6 billion in cash, cash equivalents, and current marketable securities on hand at the end of June 2022 which provides the company with ample liquidity to meet its near-term funding needs.
IBM continues to expect that its constant currency revenues will grow decently this year (in the mid-single digit range), though sustained foreign currency headwinds are expected to offset strong demand for its offerings, to a degree. Over the long haul, we forecast that under its new management team, IBM will return to stable revenue growth which in turn should see the company's free cash flows swell higher. That would allow IBM to boost its dividend in a sustainable manner going forward, though we caution that its net debt load could limit the size of any future payout increases.
The Dividend Cushion Ratio Deconstruction, shown in the image up above, reveals the numerator and denominator of the Dividend Cushion ratio. At the core, the larger the numerator, or the healthier a company's balance sheet and future free cash flow generation, relative to the denominator, or a company's cash dividend obligations, the more durable the dividend.
The Dividend Cushion Ratio Deconstruction image puts sources of free cash in the context of financial obligations next to expected cash dividend payments over the next 5 years on a side-by-side comparison. Because the Dividend Cushion ratio and many of its components are forward-looking, our dividend evaluation may change upon subsequent updates as future forecasts are altered to reflect new information.
In the context of the Dividend Cushion ratio, IBM's numerator is smaller than its denominator, which suggests weak forward-looking dividend coverage. However, given IBM's strong and stable cash flow profile, we view its forward-looking dividend coverage favorably when considering IBM's ability to tap capital markets into account. Should IBM stumble for any reason, its ability to make good on its payout may be in danger.
The best measure of a firm's ability to create value for shareholders is expressed by comparing its return on invested capital ['ROIC'] with its weighted average cost of capital ['WACC']. The gap or difference between ROIC and WACC is called the firm's economic profit spread. IBM's 3-year historical return on invested capital (without goodwill) is 41.6%, which is above the estimate of its cost of capital of 9.2%.
In the chart down below, we show the probable path of ROIC in the years ahead based on the estimated volatility of key drivers behind the measure. The solid grey line reflects the most likely outcome, in our opinion, and represents the scenario that results in our fair value estimate. Assuming IBM's recent portfolio optimization efforts go as planned, the firm's ability to generate shareholder value (which historically has been impressive) should continue to improve.
Our discounted cash flow process values each firm on the basis of the present value of all future free cash flows, net of balance sheet considerations. We think IBM is worth $136 per share with a fair value range of $101-$171 per share. Shares of IBM are trading moderately below our fair value estimate as of this writing.
The near-term operating forecasts used in our enterprise cash flow model, including revenue and earnings, do not differ much from consensus estimates or management guidance. Our model reflects a compound annual revenue growth rate of 3.4% during the next five years, a pace that is higher than the firm's 3-year historical compound annual growth rate of -10.3%.
Our model reflects a 5-year projected average operating margin of 17.6%, which is above IBM's trailing 3-year average. Beyond Year 5, we assume free cash flow will grow at an annual rate of 2% for the next 15 years and 3% in perpetuity. For IBM, we use a 9.2% weighted average cost of capital to discount future free cash flows.
Although we estimate IBM's fair value at about $136 per share, every company has a range of probable fair values that's created by the uncertainty of key valuation drivers (like future revenue or earnings, for example). After all, if the future were known with certainty, we wouldn't see much volatility in the markets as stocks would trade precisely at their known fair values.
In the graphic up above, we show this probable range of fair values for IBM. We think the firm is attractive below $101 per share (the green line), but quite expensive above $171 per share (the red line). The prices that fall along the yellow line, which includes our fair value estimate, represent a reasonable valuation for the firm, in our opinion.
The steady decline in IBM's legacy business since 2010 represents a major reason why the firm spun off Kyndryl in November 2021. Going forward, IBM will need to prove that as a leaner and more focused enterprise, it can maintain solid revenue and operating income growth over the long haul. We think that will be the case, though substantial near-term headwinds remain. Investors looking for an income generation idea backed up by a strong cash flow profile should take a closer look at IBM.
In honor of National Hispanic Heritage Month, we asked three IBM employees to share their experiences. Romelia Flores is an IBM distinguished engineer and a master inventor currently on IBM's client engineering team based in Dallas, Texas. Robert Loredo is the IBM quantum ambassador worldwide lead and a master inventor based in South Florida. Catherine Treviño is a z Hardware brand technical specialist based in Poughkeepsie, New York.
In this Q&A, these three employees open up about how mentorship has benefitted their careers and share the importance of giving back to fellow members of the Hispanic community.
Flores: I joined IBM over 30 years ago as an intern and student at the University of Texas at Austin where I obtained a degree in computer science. As a software developer, I thrive on leveraging technology to accelerate business and collaborate with clients to drive app modernization. IBM has superlative talent around the world, many of whom have guided my journey. Being a strong technologist means being a continuous learner of technology as well as establishing a strong network.
Loredo: I joined IBM in 2004 and am fortunate to have a successful career because of IBM's network and community. I have 20 years of experience in enterprise product development leveraging leading-edge technologies, most recently with quantum computing, a technology that's expected to solve intractable problems that today's most powerful classical supercomputers find challenging to solve.
Treviño: My journey at IBM has been short but accomplished! I joined in 2020 as an intern and rising senior from the University of Texas – Rio Grande Valley. Upon completing my internship, I accepted an offer and returned in 2021. I've since switched roles to a different business unit, thanks to the guidance of fellow volunteers of Hispanics@IBM, the community for Hispanic IBM employees.
Treviño: Networking led to a new opportunity within my first year at IBM. When I first joined full-time, I quickly realized the role was not the right fit. As a first-generation professional, I wasn't sure how to navigate the situation. I chatted with Alan, IBM D&I leader for the Hispanic community, who connected me with Cleo, a Hispanic executive council leader, who brought up an open role. I'm grateful for that connection! Long story short, I'm now part of Cleo's global sales team, where I help financial market clients find solutions with our z Systems.
Loredo: I'm grateful for the mentor who saw my potential and found a unique way to teach me complex subjects. While at Miami-Dade College, I struggled with the courses for engineering majors. My professor knew I enjoyed music and began teaching me mathematics using music as an analogy. That was my 'aha!' moment. My grades improved, allowing a transfer to the University of Miami, where I completed my bachelor's and master's degrees in computer engineering. That moment, when my professor found an unconventional way to teach, had a profound impact on me. I use that technique today. I wrote a book that teaches quantum computing implementation and I use analogies to explain it.
Flores: I've mentored hundreds of college students and IBM employees, including distinguished engineers and technologists. I've been told— especially by females and underrepresented minorities — that they've never seen a technologist with my level of impact, and they ask, "What's your secret to success?" This inspired me to develop the "Eight Cs: Blueprint for Success" which I believe are key attributes for attaining success: competence, communication, commitment, creativity, collaboration, confidence, community, and chuckle – we often forget about this last one, but our work should be fun!
This post was created by IBM with Insider Studios.
Quantum computing will bring unimagined innovations to the world when it finally arrives in full glory. Still, quantum remains in the research labs at companies like IBM, Google, and Microsoft. While companies and research institutions are investing billions of dollars to increase the capacity of quantum systems, a time will come in the following years, or decades, when researchers will reach "quantum supremacy." But these large quantum marvels could also jeopardize the security of critical information systems. Researchers, including IBM are working to develop new security algorithms that will be resilient to these attacks.
While quantum can solve computing challenges far beyond what is possible today, its ability to find the factors of large prime numbers makes it the ideal cybersecurity safe cracker once quantum computing systems mature in their scale, quality, and speed. Every computer system and every bit of "secure" data could become vulnerable to attack from quantum-equipped nefarious actors. The World Economic Forum "estimate(s) that over 20 billion digital devices will need to be either upgraded or replaced in the next 10-20 years to use the new forms of quantum-resistant encrypted communication. We recommend that organizations start planning for this now.”
What constitutes "adequate size" might deliver us some false comfort: a 2019 study suggested that a computer with 20 million qubits would take eight hours to break modern encryption. Today's quantum computers are on the order of only 100 qubits. But while that implies that the threat is in the distant future, one must consider that a bad actor doesn't need to wait for the massive quantum system to materialize. The "Steal now, crack later" approach leads to a latent future security threat. Consequently, organizations should deploy quantum-safe security as soon as possible to minimize future risk.
Consequently, the National Institute of Standards and Technology (NIST), a bureau of the U.S. Department of Commerce, has been conducting an ongoing search for quantum-safe security algorithms that are both secure and efficient. After all, we need our laptops, cars, and mobile phones to also be able to resist attacks from quantum-equipped bad actors. After four rounds of submissions, NIST selected four algorithms from a slate of 82 candidates. IBM Research had submitted 3 of the four chosen algorithms. All submissions have been subjected to research by industry scrutiny by government agencies, academic scientists, and mathematicians. This process is now reaching its conclusion; the NIST is expected to publish standards based on these 4 algorithms sometime in 2024.
The NIST contest covers the two aspects of security that could be vulnerable to quantum computing: public key encapsulation (used for public-key encryption and key establishment) and digital signatures (used for identity authentication and non-repudiation). For the former, NIST selected the CRYSTALS-Kyber algorithm. NIST selected three algorithms for signatures: CRYSTALS-Dilithium, FALCON, and SPHINCS+, with CRYSTALS-Dilithium as the primary algorithm in the signature category.
On September 29, GSMA announced the formation of the GSMA Post-Quantum Telco Network Taskforce, of which IBM and Vodafone are initial members, to help define policy, regulation and operator business processes to enhance protections of telecommunications in a future of advanced quantum computing. Since virtually all organizations and sectors conduct commerce on the internet, and the 800 providers whose pipes that carry all the internet traffic, the Telco industry is a good place to start. We expect other sectors to follow suit, perhaps starting with banking, government, and health care.
Given the magnitude of the potential risks, and the predominance of IBM Z systems in security-critical applications, IBM has included future-proof digital signature support in its latest z16 mainframe using CRYSTALS-Kyber and CRYSTALS -Dilithium algorithms selected by NIST. z16 implements this algorithm across multiple layers of firmware to help protect business-critical infrastructure and data from future quantum attacks. IBM has said it is also working to bring these new methods to the broader market.
In addition, IBM has developed a multi-step process to assist clients toward rapidly making institutions quantum safe. The company works with clients to identify where they are vulnerable to quantum-based cryptography attacks, assess cryptographic maturity and dependencies, and identify near-term achievable cryptographic goals and projects. The risks clients may face vary substantially based on the type of applications and data an organization handles and the state of its current cryptography.
Quantum computing's potential threat to global information security may seem to be a distant and abstract risk. However, the inevitable advances of quantum technology and the "Steal now, crack later" approach bad actors are undertaking to make quantum-safe a genuine and pressing matter for vendors and IT organizations. IBM wasted no time bringing that technology to market in the IBM z16. IBM Research has contributed three of the four algorithms the NIST quantum-safe contest has selected to be the most viable, secure, and efficient of the 70 techniques evaluated.
Beyond the NIST-approved algorithms, IBM Is working to provide “crypto agility”, helping organizations not only replace the soon-to-fail existing algorithms but also transform their security practices to remain resilient as new threats emerge in the post-quantum world. Creating crypto observability, enabling ongoing monitoring and actions on crypto-related security items, will help keep the world safer from bad actors with virtually unlimited computing capacity at their disposal.
More information can be found at here.
Disclosures: This article expresses the opinions of the authors, and is not to be taken as advice to purchase from nor invest in the companies mentioned. Cambrian AI Research is fortunate to have many, if not most, semiconductor firms as our clients, including Blaize, Cerebras, D-Matrix, Esperanto, FuriosaAI, Graphcore, GML, IBM, Intel, Mythic, NVIDIA, Qualcomm Technologies, Si-Five, SiMa.ai, Synopsys, and Tenstorrent. We have no investment positions in any of the companies mentioned in this article and do not plan to initiate any in the near future. For more information, please visit our website at https://cambrian-AI.com.
“We can‘t be essential unless our partners are skilled in our products and confident in going to their clients with our products and selling them with us and for IBM,” IBM channel chief Kate Woolley said.
IBM has started giving registered members of its PartnerWorld program access to the training, badges and enablement IBM sales employees get along with a new learning hub for accessing materials.
The expansion is part of the Armonk, N.Y.-based tech giant’s investment in its partner program, IBM channel chief Kate Woolley told CRN in an interview.
“We can‘t be essential unless our partners are skilled in our products and confident in going to their clients with our products and selling them with us and for IBM,” said Woolley (pictured), general manager of the IBM ecosystem.
[RELATED: Channel Chief Kate Woolley: ‘No Better Time To Be An IBM Partner’]
Partners now have access to sales and technical badges showing industry expertise, according to a blog post Tuesday. Badges are shareable on LinkedIn and other professional social platforms. IBM sales representatives and partners will receive new content at the same time as it becomes available.
“This is the next step in that journey in terms of making sure that all of our registered partners have access to all of the same training, all of the same enablement materials as IBMers,” Woolley told CRN. “That’s the big message that we want people to hear. And then also in line with continuing to make it easier to do business with IBM, this has all been done through a much improved digital experience in terms of how our partners are able to access and consume.”
Among the materials available to IBM partners are scripts for sales demonstrations, templates for sales presentations and positioning offerings compared to competitors, white papers, analyst reports and solution briefs. Skilling and enablement materials are available through a new learning hub IBM has launched.
“The partners are telling us they want more expertise on their teams in terms of the IBM products that they‘re able to sell and how equipped they are to sell them,” Woolley said. “And as we look at what we’re hearing from clients as well, clients want that. … Our clients are saying, ‘We want more technical expertise. We want more experiential selling. We want IBM’ – and that means the IBM ecosystem as well – ‘to have all of that expertise and to have access to all the right enablement material to be able to engage with us as clients.’”
The company has doubled the number of brand-specialized partner sellers in the ecosystem and increased the number of technical partner sellers by more than 35 percent, according to IBM.
The company’s recent program changes have led to improved deal registration and introduced to partners more than 7,000 potential deals valued at more than $500 million globally, according to IBM. Those numbers are based on IBM sales data from January 2022 to August.
Along with the expanded access to training and enablement resources, Woolley told CRN that another example of aligning the IBM sales force and partners was a single sales kickoff event for employees and partners. A year ago, two separate events were held.
“I want our partners to continue to feel and see this as a big investment in them and representative of how focused we are on the ecosystem and how invested we are,” she said.
IBM has announced the latest version of its Linux-focused mainframe - the LinuxOne Emperor 4 as the company leads with promises of reduced energy consumption and increased sustainability.
While the z16 mainframe, which was announced by the company in April 2022, is optimized for IBM’s z/OS operating system, the LinuxOne Emperor 4 is designed to support Linux operating systems in a bid to obtain a significant portion of the Linux market.
Big Blue’s latest mainframe supports 32 Telum processors and can provide up to 40TB of RAIM. The Emperor 4 also provides “seven nines” of availability, which should translate to three seconds of downtime per year.
Mainframes for Linux distros are increasingly popular among financial services organizations, with Citibank being a user of IBM’s LinuxOne mainframes, combined with the MongoDB database.
With its latest iteration, it’s clear that IBM’s focus is on increasing environmental pressures. In a release, it claims that the Emperor 4 “can reduce energy consumption by 75%, space by 50%, and the CO2e footprint by over 850 metric tons annually.”
This expression of commitment towards creating more sustainable products goes hand-in-hand with IBM’s own research which suggests that around half of the CEOs that took part saw sustainability as their highest priority, and indeed one of their greatest challenges.
The integration of artificial intelligence inference should also serve to Improve latency.
Availability for the IBM LinuxOne Emperor 4 is scheduled for September 14, 2022, with entry- and mid-range models set to follow in the first half of 2023.
A four-year bachelor’s degree has long been the first rung to climbing America’s corporate ladder.
But the move to prioritize skills over a college education is sweeping through some of America’s largest companies, including Google, EY, Microsoft, and Apple. Strong proponents say the shift helps circumvent a needless barrier to workplace diversity.
“I really do believe an inclusive diverse workforce is better for your company, it’s good for the business,” Ginni Rometty, former IBM CEO, told Fortune Media CEO Alan Murray during a panel last month for Connect, Fortune’s executive education community. “That’s not just altruistic.”
Under Rometty’s leadership in 2016, tech giant IBM coined the term “new collar jobs” in reference to roles that require a specific set of skills rather than a four-year degree. It’s a personal commitment for Rometty, one that hits close to home for the 40-year IBM veteran.
When Rometty was 16, her father left the family, leaving her mother, who’d never worked outside the home, suddenly in the position to provide.
“She had four children and nothing past high school, and she had to get a job to…get us out of this downward spiral,” Rometty recalled to Murray. “What I saw in that was that my mother had aptitude; she wasn’t dumb, she just didn’t have access, and that forever stayed in my mind.”
When Rometty became CEO in 2012 following the Great Recession, the U.S. unemployment rate hovered around 8%. Despite the influx of applicants, she struggled to find employees who were trained in the particular cybersecurity area she was looking for.
“I realized I couldn’t hire them, so I had to start building them,” she said.
In 2011, IBM launched a corporate social responsibility effort called the Pathways in Technology Early College High School (P-TECH) in Brooklyn. It’s since expanded to 11 states in the U.S. and 28 countries.
Through P-TECH, Rometty visited “a very poor high school in a bad neighborhood” that received the company’s support, as well as a community college where IBM was offering help with a technology-based curriculum and internships.
“Voilà! These kids could do the work. I didn’t have [applicants with] college degrees, so I learned that propensity to learn is way more important than just having a degree,” Rometty said.
Realizing the students were fully capable of the tasks that IBM needed moved Rometty to return to the drawing board when it came to IBM’s own application process and whom it was reaching. She said that at the time, 95% of job openings at IBM required a four-year degree. As of January 2021, less than half do, and the company is continuously reevaluating its roles.
For the jobs that now no longer require degrees and instead rely on skills and willingness to learn, IBM had always hired Ph.D. holders from the very best Ivy League schools, Rometty told Murray. But data shows that the degree-less hires for the same jobs performed just as well. “They were more loyal, higher retention, and many went on to get college degrees,” she said.
Rometty has since become cochair of OneTen, a civic organization committed to hiring, promoting, and advancing 1 million Black individuals without four-year degrees within the next 10 years.
If college degrees no longer become compulsory for white-collar jobs, many other qualifications—skills that couldn’t be easily taught in a boot camp, apprenticeship program, or in the first month on the job—could die off, too, University of Virginia Darden School of Business professor Sean Martin told Fortune last year.
“The companies themselves miss out on people that research suggests…might be less entitled, more culturally savvy, more desirous of being there,” Martin said. Rather than pedigree, he added, hiring managers should look for motivation.
That’s certainly the case at IBM. Once the company widened its scope, Rometty said, the propensity to learn quickly became more of an important hiring factor than just a degree.
This story was originally featured on Fortune.com
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WASHINGTON, Oct. 10, 2022 (GLOBE NEWSWIRE) -- Global Artificial Intelligence (AI) in Manufacturing Market was valued at USD 1,482.50 Million in 2021 and is projected to surpass the valuation of USD 17,925.50 Million by 2028 at a CAGR of 51.5% during the forecast period 2022–2028. The research on AI in the manufacturing market includes a comprehensive analysis of the global market scope, as well as regional and country-level market size, market segmentation, growth, share, competition Landscape, sales analysis, the effect of domestic and global market players, value chain optimization, trade regulations, current developments, opportunities analysis, strategic market growth analysis, product launches, and technical advancements.
The material that is shot, scattered, dropped, or detonated from any weapon, such as bombs or rockets, and more specifically, the shot, shrapnel, bullets, or shells that are fired by firearms is referred to as AI in Manufacturing. AI in Manufacturing can be thought of as both a throwaway weapon and the components of other weapons responsible for producing the effect on a target. AI in manufacturing can take on a wide variety of shapes and sizes, and it is frequently developed with the sole purpose of functioning within particular sorts of weaponry.
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Artificial Intelligence is the branch of computer science that deals with making smart machines that requires human intelligence. Artificial Intelligence is believe to be the gamechanger in the industry of manufacturing. The rising adoption of Industrial 4.0 is likely to drive the growth of the market in the upcoming years. In manufacturing plants, the information obtained from various sensors, software’s, IOT driven system may become complex for human to analyse, in such situation use of Artificial Intelligence is the most efficient solution. In addition to Artificial Intelligence, with the help of Machine learning and pattern recognition, the manufacturing sector can transform completely. The use of AI in Manufacturing Market plant allows the user to analyse and predict consumer behaviour, predict preventive maintenance to prevent unwanted shutdown, detect abnormalities in production process and much more. AI also facilitates the use of real time information which could improves the decision-making time boosting the growth of organization. Moreover, increasing volume of data gathered through various devices, coupled with the widespread availability of high-speed broadband networks and the upcoming implementation of 5G technologies will further contribute to the global AI in Manufacturing Market in the coming years. Whereas, the lack of skilled expertise and infrastructure and high operation along with lack of awareness are some of the factor that are about to hamper the growth of AI in Manufacturing Market.
Key Insights & Findings from the Report:
According to our primary respondents’ research, the AI in Manufacturing market is predicted to grow at a CAGR of roughly 51.5% during the forecast period.
The AI in Manufacturing market was estimated to be worth roughly USD 1,482.50 Million in 2021 and is expected to reach USD 17,925.50 Million by 2028; based on primary research.
On the basis of region, Asia-Pacific is projected to dominate the worldwide AI in Manufacturing market.
List of Prominent Players in the Global AI in Manufacturing Market:
NVIDIA Corporation (US)
IBM Corporation (US)
Alphabet Inc. (Google) (US)
Microsoft Corporation (US)
Intel Corporation (US)
Siemens AG (Germany)
General Electric Company (US)
General Vision Inc. (US)
Progress Software Corporation (US)
Micron Technology Inc. (US)
Mitsubishi Electric Corporation (Japan)
Sight Machine (US)
Cisco Systems Inc. (US)
SAP SE (Germany)
Rockwell Automation Inc. (US)
AIBrain Inc. (US)
Vicarious Inc. (US)
Oracle Corporation (US)
Amazon Web Services (US)
Spark Cognition Inc. (US)
Rethink Robotics (Germany)
UBTECH Robotics Corp. (China)
Aquant Inc. (Israel)
Bright Machines (US)
Flutura Decision Sciences & Analytics (India)
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The AI in Manufacturing Market is segmented as below:
Offering (Hardware, Software, Services).
Technology (Machine Learning, Natural Language Processing, Context-aware Computing, Computer Vision).
Application (Predictive Maintenance and Machinery Inspection, Material Movement, Production Planning, Field Services, Quality Control, Cybersecurity, Industrial Robots, Reclamation).
Industry (Automobile, Energy and Power, Pharmaceuticals, Heavy Metals and Machine Manufacturing, Semiconductors and Electronics, Food & Beverages, Others).
Driver- Increase in adoption in AI technology for production optimization
Industries like automobiles, chemical, electronics, food among others are witnessing the need for production optimization due to competitive environment. Artificial intelligence and Machine Learning the two powerful tools to minimize the consumption of resources in every industrial process and maximize the output by optimizing the power consumption. AI and ML are build a statistical model using available data from various sensors, material used in manufacturing and various software’s. Based on this data it predicts the accurate parameter for final product resulting in saving extra material and additional resources in the production process. This enables the business to make the production cost effective.
Driver-Implementation of Industrial 4.0
The influence of industrial 4.0 on the manufacturing sector is tremendous. With 4.0 the industries are getting smarter by adoption of smart sensors, interconnected systems, and others. But due to this a large amount of data is exchanged among the machines. To handle such large amount of data, Artificial intelligence is the best choice as it facilitates intelligent manufacturing. Intelligent manufacturing uses AI based data driven model that that takes manufacturing decision, prediction and real time optimization in manufacturing process. Hence, driving the growth of the AI in Manufacturing Market.
The implementation of AI requires skilled labour who can handle the entire process right from start to end. The concerned person should have in depth knowledge about AI, its behaviour, implementation and limitation. Thus, lack of skill and knowledge whether AI can handle the entire process or not is what hampering the growth of AI.
A potential barrier to adoption of AI technology is the manufacturer lack of trust in its capabilities. People without relevant education background often struggle to understand the working model of technology and do not have full confidence in its working.
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Asia Pacific is estimated to be the largest shareholder for the Global AI in Manufacturing Market due to the presence of large number of manufacturing companies in China, India, Japan and South Korea and their rising focus on digitalization and technological advancement. Also, the government of India, China, Japan and Singapore are investing in technologies like AI and boosting its use in manufacturing sector and for industries 4.0. China’s implementation of AI is very high. The initiative of Indian government like Make in India is motivating the manufacturing sector and startup’s to use advanced technology like AI. The government of Singapore is inviting private firm’s investment to test AI functionality for the country.
Europe is estimated to be the next biggest shareholder after India, because of countries like UK which are making a huge investment in R&D of advanced technologies like AI. Also, the latest guidelines of government of Italy for the public about the National Strategy in Artificial Intelligence is likely to boost the use of AI in the region. North America, on the other hand, will witness significant growth owing to increasing investment in R&D activities and a growing number of startup’s for AI technology.
February 2022, IBM Corporation announced the launch of the IBM Sustainability Accelerator, a global pro bono social impact program that applies IBM technologies, such artificial intelligence, and an ecosystem of experts to enhance and scale non-profit and government organization operations, focused on populations vulnerable to environmental threats including climate change, extreme weather, and pollution.
March 2020, Siemens collaborated with NEC to provide manufacturing industries solutions and AI monitoring to accelerate digitalization
July 2019, Microsoft partnered and invested $1billion in company named OpenAI. OpenAI enhance Azure platform and build next gen application. Azure will thus be working on running AI technologies.
The report on the Global AI in Manufacturing Market highlights:
Assessment of the market
COVID Impact Analysis
Historic Data, Estimates, and Forecast
Global and Regional Dynamics
Key Questions Answered in The Report:
What is AI in Manufacturing?
How big is the AI in Manufacturing market?
What is AI in Manufacturing product use for?
Who are the key players in the AI in Manufacturing market?
What is the scope of growth in the AI in Manufacturing market?
What are the key trends in the AI in Manufacturing market report?
What is the core strategy for growth in the AI in Manufacturing market?
Which is base year calculated in the AI in Manufacturing market report?
What are the risks involved in investing in the AI in Manufacturing market?
What are the main opportunities for growth in the AI in Manufacturing market?
What are the core strategies of key players in the AI in Manufacturing market?
This market titled “Global AI in Manufacturing Market” will cover exclusive information in terms of Geographic Segmentation, Forecast, Regional Analysis, Key Market Trends, and various others as mentioned below:
Market Size in 2021
USD 1,482.50 Million
Revenue Forecast by 2028
USD 17,925.50 Million
51.5% From 2022 – 2028
° Machine Learning
° Natural Language Processing
° Context-aware Computing
° Computer Vision
° Predictive Maintenance and Machinery Inspection
° Material Movement
° Production Planning
° Field Services
° Quality Control
° Industrial Robots
° Energy and Power
° Heavy Metals and Machine Manufacturing
° Semiconductors and Electronics
° Food & Beverages
Region & Counties Covered
• North America
° Rest Of Europe
• Asia Pacific
° South Korea
° South East Asia
° Rest Of Asia Pacific
• Latin America
° Rest Of Latin America
• Middle East & Africa
° GCC Countries
° South Africa
° Rest Of Middle East & Africa
• NVIDIA Corporation (US)
• IBM Corporation (US)
• Alphabet Inc. (Google) (US)
• Microsoft Corporation (US)
• Intel Corporation (US)
• Siemens AG (Germany)
• General Electric Company (US)
• General Vision Inc. (US)
• Progress Software Corporation (US)
• Micron Technology Inc.(US)
• Mitsubishi Electric Corporation (Japan)
• Sight Machine (US)
• Cisco Systems Inc. (US)
• SAP SE (Germany)
• Rockwell Automation Inc. (US)
• AI Brain Inc. (US)
• Vicarious Inc. (US)
• Oracle Corporation (US)
• Amazon Web Services (US)
• Spark Cognition Inc. (US)
• Rethink Robotics (Germany)
• UBTECH Robotics Corp. (China)
• Aquant Inc. (Israel)
• Bright Machines (US)
• and Flutura Decision Sciences & Analytics (India).
Market growth drivers, restraints, opportunities, Porter’s five forces analysis, PEST analysis, value chain analysis, regulatory landscape, technology landscape, patent analysis, market attractiveness analysis by segments and North America, company market share analysis, and COVID-19 impact analysis
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RESEARCH TRIANGLE PARK – In a move to enhance its hybrid cloud and AI capabilities, IBM will buy the digital product engineering consulting services firm Dialexa in a deal that will close later this year.
IBM announced the deal in a statement, which also notes that the purchase of the firm will “deepen IBM’s product engineering expertise and provide end-to-end digital transformation services for clients.”
When the deal closes, Dialexa will become the sixth company bought by IBM in 2022.
But Big Blue has been on a buying frenzy since April 2020, when Arvind Krishna became the company’s CEO. According to the company, IBM has acquired more than 25 other firms, with 13 to bolster IBM Consulting.
The latest acquisition of Dialexa points toward how IBM may grow its consulting services presence.
“In this digital era, clients are looking for the right mix of high-quality products to build new revenue streams and Improve topline growth,” said John Granger, senior vice president, IBM Consulting, in a statement. “Dialexa’s product engineering expertise, combined with IBM’s hybrid cloud and business transformation offerings, will help our clients turn concepts into differentiated product portfolios that accelerate growth.”
The company’s 300 employees are based in Dallas and in Chicago, and will join IBM Consulting, according to the statement. Among the firm’s clients is Toyota Motor North America, which will invest $2.5 billion in North Carolina to build the company’s first U.S. electric battery manufacturing plant in Randolph County.