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Exam Code: M2090-643 Practice exam 2022 by team
Information Management Solution Sales Mastery Test v4
IBM Information Topics
Killexams : IBM Information Topics - BingNews Search results Killexams : IBM Information Topics - BingNews Killexams : Top IBM Shareholders

International Business Machines Corp. (IBM) was founded more than a century ago, in 1911, as the Computing-Tabulating-Recording Company (C-T-R). But the computer giant traces its roots back to the1880s. During that decade, Dr. Alexander Dey invented the first dial recorder for his business, while a second enterprise, Bundy Manufacturing, became the first time recording company. Both companies became key building blocks of C-T-R. 

More recently, IBM has become a global information technology company focused on software, cloud computing, and consulting services. IBM primarily generates revenue today through its five segments: Cloud & Cognitive Software; Global Business Services; Global Technology Services; Systems; and Global Financing.

The top shareholders of IBM are James Whitehurst, Arvind Krishna, James Kavanaugh, Vanguard Group Inc., BlackRock Inc., and State Street Corp.

As of January 5, 2021, IBM had trailing 12-month (TTM) revenue of $75.0 billion and TTM net income of $7.9 billion, with a market capitalization of $111.4 billion.

Below, we take a closer look at the top shareholders of IBM.

"Insider" refers to people in senior management positions and members of the board of directors, as well as people or entities that own more than 10% of the company's stock. In this context, it has nothing to do with insider trading.

Top 3 Individual Insider Shareholders

James M. Whitehurst

James M. Whitehurst owns 148,606 shares of IBM, representing 0.02% of all outstanding shares. Whitehurst has been president of IBM since 2020. In this role, he is responsible for IBM Cloud and Cognitive Software organization and Corporate Strategy. Prior to IBM, Whitehurst was president and CEO of Red Hat, the open source enterprise software company, and earlier in his career was chief operating officer of Delta Airlines. Whitehurst played a key role in driving IBM's high-profile, $34-billion acquisition of open-source software company Red Hat, the largest such purchase in the company’s history.

Arvind Krishna

Arvind Krishna owns 86,188 shares of IBM, representing 0.01% of all outstanding company shares. Krishna became CEO of IBM in April of 2020 after serving as senior vice president of Cloud and Cognitive Software, IBM’s fastest growing business. He joined IBM in 1990 as a member of the company’s Watson Research division, then becoming general manager of IBM Systems and Technology Group’s development and manufacturing organization. Krishna has been a key driver of IBM’s push into cloud computing in accurate years, and as head of IBM Research, he has guided the company through developments into blockchain, artificial intelligence, and quantum computing technologies. Krishna was a major architect of IBM’s acquisition of Red Hat.

James J. Kavanaugh 

James J. Kavanaugh owns 77,541 shares of IBM, representing 0.01% of all outstanding company shares. Since 2018, Kavanaugh has been senior vice president and chief financial officer of IBM, overseeing the company’s global financial operations. In these roles he also leads the company’s Global Financing business. Kavanaugh joined IBM in 1996 and has held a variety of financial leadership roles for the company, including vice president of finance for the Americas Group and IBM EMEA. From 2008 to 2015, he was IBM’s controller and from 2015 to 2018, he was senior vice president, Transformation & Operations. In his current role he continues to oversee Transformation & Operations, leading the company in aligning its operating model with fundamental industry shifts. Prior to IBM, Kavanaugh was chief financial officer for the Americas Global Services unit at AT&T Corp.

Top 3 Institutional Shareholders

Institutional investors hold the majority of IBM shares at about 51.9% of total shares outstanding.

Vanguard Group Inc. 

Vanguard Group owns 74.2 million shares of IBM, representing 8.3% of total shares outstanding, according to the company's 13F filing for the period ending September 30, 2020. The company is primarily a mutual fund and ETF management company with about $6.2 trillion in global AUM. The Vanguard Information Technology ETF (VGT), which tracks a market-cap-weighted index of IT companies, owns IBM. The company represents about 1.1% of the fund's portfolio.

BlackRock Inc.

BlackRock owns 60.9 million shares of IBM, representing 6.8% of total shares outstanding, according to the company's 13F filing as of September 30, 2020. The company is primarily a mutual fund and ETF management company with approximately $7.8 trillion in AUM. The iShares MSCI USA Value Factor ETF (VLUE), which invests in undervalued large- and mid-cap companies, owns IBM. IBM is the fourth-largest holding at 3.2% of the fund's portfolio.

State Street Corp. 

State Street owns 53.0 million shares of IBM, representing 5.9% of total shares outstanding, according to the company's 13F filing as of September 30, 2020. State Street manages mutual funds, ETFs and other investments with $3.1 trillion in AUM. The SPDR Dow Jones Industrial Average ETF Trust (DIA), which tracks a price-weighted index of 30 large-cap U.S. stocks, holds IBM. IBM represents 2.7% of the fund's holdings.

Wed, 19 Oct 2016 05:45:00 -0500 en text/html
Killexams : IBM Made a 'Crash Course' For The White House, And It'll Teach You All The AI Basics

Alarmed by the AI Revolution

Vernor Vinge once stated in his book The Singularity, “We are on the edge of change comparable to the rise of human life on Earth.” As AI now undoubtedly plays a pivotal role in many industries, its risks and repercussions simply cannot be ignored; and shining a light upon these has never been more imperative.

That's why, in response to the White House's Notice Of Request For Information (RFI), IBM has created what seems to be an AI 101—covering the huge field of AI and its vast potential applications.

Image Credit: Futuristech

"The views of the American people, including stakeholders such as consumers, academic and industry researchers, private companies, and charitable foundations, are important to inform an understanding of current and future needs for AI in diverse fields," the RFI summary read.

Responding to Skepticsm

IBM's AI 101 consisted of a numbered list of Topics in a somewhat re-ordered and slightly re-factored response to the RFI's questions. As Techcrunch suggests, each subject is explained well enough to make readers the smartest in the room. The following are the Topics in IBM's response:

  1. The use of AI for public good
  2. Social and economic implications of AI 
  3. Education for harnessing AI technologies 
  4. Fundamental questions in AI research, and the most important research gaps
  5. Data sets that can accelerate AI research 
  6. Multi-disciplinary research 
  7. Role of incentives and prizes 
  8. Safety and control issues for AI 
  9. Legal and governance implications of AI
  10. Other issues: Business models 

In hindsight, even though there are many ambiguities and inefficiencies associated with the AI revolution, IBM believes that these can be eliminated and that "AI systems...will ultimately transform our personal and professional lives. Its benefits far outweigh its risks. And with the right policies and support, those benefits can be realized sooner."

Sat, 06 Aug 2016 02:27:00 -0500 text/html
Killexams : 6 Companies Owned by IBM

International Business Machines Corp. (IBM) is a multinational technology company that offers a range of computing solutions and technology consulting services. Big Blue traces its origins back as early as the 1880s, but it was in 1911 that the company was first incorporated as the Computing-Tabulating-Recording Co. (C-T-R) in the state of New York.

C-T-R manufactured and sold a range of machinery, including commercial scales, industrial time recorders, meat and cheese slicers, tabulators, and punched cards. The company formally changed its name to its current name in 1924 and has since grown into a major global corporation focused on software, technology and business consulting, and cloud computing.

IBM generated annual net income of $5.6 billion on revenue of $73.6 billion in 2020. It has a market capitalization of $125.3 billion as of July 13, 2021. It currently operates through five business segments: Cloud & Cognitive Software, Global Business Services, Global Technology Services, Systems, and Global Financing.

IBM’s early history is marked by its focus on the manufacture of machinery and computer hardware products. But beginning around the 1990s, the company began to shift its focus toward computer services and software. It sold off hardware businesses, such as flat-panel displays, disk drives, and personal computers, while simultaneously acquiring services and software companies. In accurate years, the company has set its sights on becoming a leader in cloud computing, a strategic push underscored by its 2019 acquisition of Red Hat Inc. To facilitate this shift toward cloud services and artificial intelligence (AI), IBM has announced that it will spin off its infrastructure management business. The new company will be called Kyndryl, and the spin-off is expected to be complete by the end of 2021.

Below, we take a closer look at six of IBM’s more accurate acquisitions, all of which have taken place within the past 20 years. The company does not provide a breakdown of how much profit or revenue each acquisition currently contributes, except for quarterly revenue for Red Hat. 

Red Hat Inc.

  • Type of business: Open source software
  • Acquisition price: Approximately $34 billion
  • Acquisition date: July 9, 2019

Red Hat was founded in 1993 by Marc Ewing, or, as he was known by many in the computer lab during college, “the guy in the red hat.” Ewing had created and was distributing his own version of Linux® on CDs. He later joined forces with small businessman Bob Young and the two launched Red Hat Software in 1995, with Young as CEO. The open source development model on which the company was built was aimed at challenging what its founders saw as the monopolistic tendencies of the technology industry. The company went public in 1999 with a record-breaking initial public offering (IPO).

In 2019, Red Hat was acquired by IBM for approximately $34 billion, which broke the record for the largest software acquisition in history. The acquisition brings together Red Hat’s open hybrid cloud technologies with the scale and depth of IBM’s innovation, industry expertise, and sales leadership. The goal for IBM has been to work with Red Hat in offering a next-generation hybrid multi-cloud platform for its enterprise clients, especially as some of IBM’s legacy businesses are shrinking.

Cognos Inc.

  • Type of business: Business intelligence and performance management software
  • Acquisition price: $4.9 billion
  • Acquisition date: Jan. 31, 2008

Cognos was founded in 1969 by Alan Rushforth and Peter Glenister in Ottawa, Canada. The firm specialized in developing software for business intelligence and performance management. In 2005, Cognos launched its award winning BI 8 product, which could be used for creating professional reports, data analysis and monitoring, model creation, and more.

The company was acquired by IBM in 2008 for $4.9 billion. At the time, IBM’s intention in acquiring Cognos was to accelerate its cross-company Information on Demand strategy, unlocking the business value of information through information integration, content and data management, and business consulting services. The combination would help companies increase the value of their information, optimize business processes, and maximize performance. 

SoftLayer Technologies Inc.

  • Type of business: Cloud computing infrastructure
  • Acquisition price: Financial terms were not disclosed but were estimated at $2 billion
  • Acquisition date: July 8, 2013

SoftLayer Technologies was founded in 2005 as a hosting services and cloud computing provider. By the time SoftLayer was acquired by IBM in 2013, it had about 21,000 customers and was operating 13 data centers in the United States, Europe, and Asia.

Following the acquisition, SoftLayer became part of IBM’s cloud services division. The aim of the combination was to create a global cloud platform that would make it easier for companies and organizations to adopt the latest cloud services. It was another example of IBM’s push to accelerate the growth of its cloud computing business since it began making more than a dozen cloud-related acquisitions starting in 2007. SoftLayer, now called IBM Cloud, currently has more than 60 data centers in 19 countries. 

PricewaterhouseCoopers (PwC) Consulting

  • Type of business: Global management consulting and technology services
  • Acquisition price: Approximately $3.5 billion
  • Acquisition date: Oct. 2, 2002

PricewaterhouseCoopers, a global network of firms offering assurance, tax, and consulting services, was created out of a 1998 merger between Price Waterhouse and Coopers & Lybrand. In 2002, the company sold its consulting services business—PwC Consulting—to IBM for approximately $3.5 billion.

IBM integrated the consulting service into a new global business unit called IBM Business Consulting Services, extending the reach of its Global Services Business. At the time, it was the largest consulting services organization in the world, having operations in more than 160 countries. The acquisition allowed IBM to combine business consulting with technology solutions, which many of its clients were demanding at the time.

Truven Health Analytics

  • Type of business: Cloud-based healthcare data, analytics, and insights
  • Acquisition price: $2.6 billion
  • Acquisition date: April 8, 2016

Healthcare data and analytics services company Truven Health Analytics was formerly the healthcare unit of Thomson Reuters Corp. (TRI). Veritas Capital Fund Management LLC bought the healthcare unit from Thomson Reuters for $1.25 billion in 2012 and rebranded it as Truven Health Analytics. Several years later, Truven became a target in IBM’s aggressive push into the healthcare industry. IBM bought the healthcare analytics company in 2016 after making several acquisitions of medical technology companies totaling more than $4 billion over the previous year.

The Truven acquisition provided IBM with a massive new body of data, enabling IBM to expand the capabilities of its Watson AI system. AI machine learning systems such as Watson require large amounts of data from which they are trained to identify and extract useful patterns. The deal also was expected to double the size of IBM’s healthcare business. Truven has since become fully integrated into IBM Watson Health, which provides solutions to the healthcare industry.


  • Type of business: Artificial intelligence and information technology management
  • Acquisition price: Reportedly over $1.5 billion
  • Acquisition date: June 17, 2021

Turbonomic was founded in 2009 with the goal of developing AI software to manage information technology (IT) systems. The company provides an analytics engine to oversee resourcing decisions and facilitate communication among systems. The company has grown to serve thousands of customers, including a third of Fortune 500 companies.

IBM announced the closing of its acquisition of Turbonomic in June 2021 as part of its new focus on cloud services and AI. This acquisition comes amid a flurry of deals around other cloud and AI companies, including Nordcloud and Instana.

Thu, 18 Jan 2018 01:12:00 -0600 en text/html
Killexams : IBM- Security and Privacy services News No result found, try new keyword!Illumio collaborates with IBM Security to bolster cyber resilience for modern organisations ... standards and measures. Timely and newsworthy Topics are included as a means of educating attendees on ... Sat, 19 Mar 2022 02:41:00 -0500 text/html Killexams : Machine Learning and Artificial Intelligence in the Enterprise

Predictive analytics / machine learning / artificial intelligence is a hot subject - what's it about?

Using algorithms to help make better decisions has been the "next big thing in analytics" for over 25 years. It has been used in key areas such as fraud the entire time. But it's now become a full-throated mainstream business meme that features in every enterprise software keynote - although the industry is battling with what to call it.

It appears that terms like Data Mining, Predictive Analytics, and Advanced Analytics are considered too geeky or old for industry marketers and headline writers. The term Cognitive Computing seemed to be poised to win, but IBM's strong association with the term may have backfired - journalists and analysts want to use language that is independent of any particular company. Currently, the growing consensus seems to be to use Machine Learning when talking about the technology and Artificial Intelligence when talking about the business uses.

Whatever we call it, it's generally proposed in two different forms: either as an extension to existing platforms for data analysts; or as new embedded functionality in diverse business applications such as sales lead scoring, marketing optimization, sorting HR resumes, or financial invoice matching.

Why is it taking off now, and what's changing?

Artificial intelligence is now taking off because there's a lot more data available and affordable, powerful systems to crunch through it all. It's also much easier to get access to powerful algorithm-based software in the form of open-source products or embedded as a service in enterprise platforms.

Organizations today have also more comfortable with manipulating business data, with a new generation of business analysts aspiring to become "citizen data scientists." Enterprises can take their traditional analytics to the next level using these new tools.

However, we're now at the "Peak of Inflated Expectations" for these technologies according to Gartner's Hype Cycle - we will soon see articles pushing back on the more exaggerated claims. Over the next few years, we will find out the limitations of these technologies even as they start bringing real-world benefits.

What are the longer-term implications?

First, easier-to-use predictive analytics engines are blurring the gap between "everyday analytics" and the data science team. A "factory" approach to creating, deploying, and maintaining predictive models means data scientists can have greater impact. And sophisticated business users can now access some the power of these algorithms without having to become data scientists themselves.

Second, every business application will include some predictive functionality, automating any areas where there are "repeatable decisions." It is hard to think of a business process that could not be improved in this way, with big implications in terms of both efficiency and white-collar employment.

Third, applications will use these algorithms on themselves to create "self-improving" platforms that get easier to use and more powerful over time (akin to how each new semi-autonomous-driving Tesla car can learn something new and pass it onto the rest of the fleet).

Fourth, over time, business processes, applications, and workflows may have to be rethought. If algorithms are available as a core part of business platforms, we can provide people with new paths through typical business questions such as "What's happening now? What do I need to know? What do you recommend? What should I always do? What can I expect to happen? What can I avoid? What do I need to do right now?"

Fifth, implementing all the above will involve deep and worrying moral questions in terms of data privacy and allowing algorithms to make decisions that affect people and society. There will undoubtedly be many scandals and missteps before the right rules and practices are in place.

What first steps should companies be taking in this area?

As usual, the barriers to business benefit are more likely to be cultural than technical.

Above all, organizations need to make sure they have the right technical expertise to be able to navigate the confusion of new vendors offers, the right business knowledge to know where best to apply them, and the awareness that their technology choices may have unforeseen moral implications.

[This article originally appeared on the Business Analytics and Digital Analytics Blog]

Sun, 26 Jun 2022 08:24:00 -0500 en text/html
The Reputational Impact of IT Risk

Summary: A major part of the brand experience for most customers comes through the technology that delivers or supports the business. When that technology doesn’t work, it’s not just a problem for the tech team; an organization’s reputation can suffer, and reputation is a board-level concern. How can companies better protect their reputation by ensuring the continuous—and secure—flow of information to support their business?

To find out, Forbes Insights conducted in-depth interviews with 10 experts and senior executives, adding context to data previously gathered for IBM.

To get a pdf of the study, please fill out the following information. If you experience any trouble, please send an email to:

Notice:  By supplying my contact information, I authorize Forbes Insights and the report sponsor to contact me about the sponsor's products and services.  Forbes Insight may use data I have provided in accordance with the Forbes online privacy policy.  

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Tue, 18 Aug 2020 03:09:00 -0500 text/html
Killexams : Cybersecurity: Why We’re Stronger Together

Advocating for greater security collaboration between businesses, law enforcement, and government

By Nicole Mills, Exhibition Director at Infosecurity Group

Cybercrime is on an extremely worrying trajectory.

A previous survey of global IT security decision makers conducted by Statista revealed that 46.4% of organizations had endured between one and five successful cyber-attacks in the 12 months ended November 2020. Since then, Accenture has reported that such attacks increased 31% between 2020 and 2021.

As we now move through 2022, this concerning reality is further compounded by even more frightening figures.

According to IBM, the average cost of a data breach last year was $4.24 million, and this number is predicted to rise in 2022. Resultantly, Cisco and Cybersecurity Ventures together suggest that come 2025, the global cost of cybercrime could exceed $10 trillion.

The Infosecurity Group Advisory Council comprising industry leaders at the cutting edge of cybersecurity solution highlight many varying factors contributing to this broad and growing challenge.

Unsurprisingly, ransomware was pinpointed as an area of particular concern. While individuals, criminal groups and nation states will continue to favour ‘tried and tested’ approaches, they are expected to employ these in novel ways to generate revenue from attacks.

Indeed, more sophisticated attacks leveraging new methodologies are becoming more commonplace, and supply chain attacks have emerged as a prime example. Businesses now need to realise that their security relies on a web of third-party suppliers, and that they’re only as strong as the weakest link.

At the same time, the council affirmed that information security investment is, generally, still not sufficiently prioritised within businesses or government.

Greater collaboration is critical

The point is that there are a multitude of evolving threats, and attitudes and mindsets simply must change in order to keep up.

Cybercriminal networks today are expanding, evolving, advancing and working together to target victims more successfully than ever before. Ransomware-as-a-service, for example, is dramatically lowering the barriers-to-entry for attackers, with savvy cybercriminals actively supporting the threat ambitions of less technically abled perpetrators at scale.

To even stand a chance in the fight taking place amid this increasingly complicated landscape, cybersecurity professionals must equally collaborate by sharing knowledge and experiences to support each other in identifying vulnerabilities and developing stronger security strategies.

Promisingly, there is agreement within our community that greater cooperation will help.

According to an Infosecurity Europe Twitter poll conducted in January 2022, 45% of the 2,543 respondents pointed to advanced threat detection is the cybersecurity challenge that would benefit most from increased industry collaboration. This was followed by social engineering threats (22%), incident response planning (18%), and governance, risk and compliance (15%).

With a clear appreciation that greater collaboration within cybersecurity will bring major advantages, it’s vital that we act as a united industry to overcome any barriers that might be stifling this. I believe we must work together to build an environment of trust and transparency where we can exchange knowledge, resources and ideas to combat security threats while protecting commercial sensitivities.

Events as pillars of security progress

It is for this reason that we chose Stronger Together as the theme for Infosecurity Europe 2022 – to try to encourage greater collaboration between businesses, law enforcement and government.

Over the years I’ve seen first-hand the vital role that events play in facilitating cross-sector cooperation, instigating vital discussions that sew the seeds of greater security progress.

Every organisation from every operational background has a unique vantage point – different approaches that have been moulded by different experiences. By exchanging these experiences, approaches and ideas, we can support each other in achieving best practice, gaining practical and actionable knowledge that can help in keeping up with the increasing sophistication of security threats.

Events are vital platforms from which we can achieve a great deal. From seasoned professionals to those just starting out, everyone has value to add, and everyone can benefit.

In the case of Infosecurity Europe 2022, Topics will range from everything from the need to tackle insider threats, building a security culture, the paradigm change in ransomware and monetisation of threats to cybercrime-as-a-service (CaaS), third party risk, how cyber criminals are changing their approaches, and improving detection of known and unknown threats.

Covering all these bases is critically important. When it comes to security, there are always more opportunities to learn. By expanding our collective knowledge, sharing insights and advocating for the broad adoption of best practices, we can begin to tackle the escalating problems of cybercrime and turn the tide together as a unified industry.

About the Author

Nicole Mills AuthorNicole Mills is Exhibition Director for the Infosecurity Group. With over 20 years’ experience in events and media, she has worked with many brands responsible for strategic and commercial growth. Nicole has worked in the Infosecurity Group for six years working with the Infosec team responsible for Infosecurity Europe and Infosecurity Magazine. Working with the team the aim is to bring the cyber community together to showcase the latest products and solutions to enable businesses to continue to protect themselves.

Nicole can be reached online at and at our company website

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Sat, 06 Aug 2022 21:00:00 -0500 en-US text/html
Killexams : The Benefits And Risks Of Embracing AI

Kevin Markarian is the cofounder of Roopler, an AI-driven lead generation platform built for the real estate industry.

Artificial intelligence is rapidly upending how people do business across industries, and yet skeptics still abound. But is there really a reason to fear AI?

AI will change how we work and do business, and its impact is already being felt. Still, that doesn’t mean it is something to fear. On the contrary, business managers and leaders who embrace AI and harness its potential now have everything to gain.

Making Sense Of AI

According to IBM, at its most basic, AI is anything that “leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind.” But not all AI is built alike. There are two types of AI: narrow AI and strong AI.

Narrow AI is trained to perform specific tasks. A bot that can carry out a conversation with a potential customer is an example of narrow AI but is more robust. Strong AI, which is what we’re moving toward, is AI that can perform all the complex tasks and decision-making processes of a human (e.g., an emotionally intelligent machine that can make tough decisions, reflect on their impact, and recalibrate accordingly). Whether strong AI is just another flying car is yet to be seen.

From Flying Cars To AI

As history has repeatedly shown, some visions of the future simply never come to pass. The first patent for a flying car was issued in 1918, and over a century later, we’re still not battling aerial car crashes. This hasn’t prevented people from dreaming and worrying about a future where skyways replace roadways. As a cofounder of a business powered by AI, my best guess is that AI is today’s flying car.

Since 2010, concerns about AI’s pending impact on the economy and the future of work have been on the rise. Unless you’ve been living off the grid, you’ve probably read dozens of articles on the subject by now, such as the 2020 article in Time that reported, “AI job automation has already replaced around 400,000 factory jobs in the U.S. from 1990 to 2007, with another 2 million on the way.”

The Time article isn’t factually incorrect. Some industries have experienced job losses, and I think more job losses might be coming. The article is also right to note that AI enables companies to do more with less. But this doesn’t mean that our jobs are threatened.

For example, consider the real estate industry. Today, AI is beginning to take over some aspects of lead generation and cultivation. While this may appear to be a threat, as someone who runs two successful brokerages and a tech company, I can assure you that the need for human agents isn’t disappearing. AI will help agents serve more consumers, but I don’t foresee anyone closing a deal on a home with a bot. Why? Because AI lacks the emotional intelligence and complexity required to help people make significant decisions, including buying and selling homes.

How Business Leaders Can Leverage AI

While AI may seem out of reach, even small- to medium-sized business owners can embrace AI.

• Leverage AI for lead generation. No one loves bad bots, but with a small investment and the right talent, you can already build AI-backed platforms that actually work. If you’re in a fast-paced, customer-focused industry like real estate or any other high-stakes sales industry, investing in AI can help you quickly respond to incoming client inquiries and close more deals over time.

• Use AI to find and recruit talent. Hiring great talent and building outstanding teams takes time and energy. With the capacity to sort through thousands of applications at a rate much faster than any human, AI is changing how we recruit talent. Better yet, it can help us discover candidates we may have overlooked in the past due to our own biases and assumptions. While AI isn't perfect (biases can be built into algorithms), it still holds the potential to help business owners cast their net wider, review more candidate applications and use increasingly nuanced criteria to recruit and build the very best talent pool.

• Let AI show you the way forward. Used to its full potential, AI can also point you and your business in entirely new directions, and for a simple reason. When you embrace AI, you have access to massive amounts of data about your customer base. You could use this information to keep doing what you're already doing, but the smartest business leaders let their AI point them in new directions.

Common Mistakes Made By New Adopters

We’ve all heard the saying, “If you can’t beat them, join them.” This also holds true for AI. AI isn’t going away. Business owners who embrace AI now and start exploring how it can help them do more will be the biggest winners. Still, it is also important to avoid these three common mistakes.

Not recruiting the right talent to your team. If you're not already using AI, you likely don't have the right talent on your team. While outsourcing an AI initiative is always an option, your return on investment will ultimately be higher if you build your AI project in-house. This likely means recruiting new talent.

Not appreciating the potential risks of investing in AI. AI also poses unique risks. If you invest in a new factory and the gamble doesn't pay off, you can still sell the factory and the equipment in it to recuperate part of your lost investment. If you invest in AI and the gamble doesn't pay off, it is a different story since you likely can't sell your algorithms, which were developed specifically for your business. In this respect, AI, for all its benefits, also poses unique risks to business owners.

Assuming AI can do it all. Finally, it is important to keep AI in perspective. It can transform your business, but this doesn't mean you can put your business on autopilot. Even as AI transforms businesses, business leaders are still calling the shots.

Over the coming decades, AI will profoundly change how we live, learn and do business. But it won't do any of this without our vision, insights and permission. As business leaders, the most strategic thing we can do is embrace AI as an opportunity to serve our broader business mandates.

Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?

Tue, 26 Jul 2022 23:15:00 -0500 Kevin Markarian en text/html
Killexams : Article: HR influencers who are changing the game in 2022 (Part 1) No result found, try new keyword!These HR influencers have inspired change in the industry creating new benchmarks and recommending to employers the best practices to overcome recruitment and leadership challenges ... Mon, 25 Jul 2022 15:45:00 -0500 en-US text/html Killexams : Ice cream maker Kemps fitting up warehouse space on former IBM campus

ROCHESTER — Maybe it's time for a new flavor: Big Blue-berry.

Two of Rochester’s biggest corporate names – Kemps and IBM – will soon come together as the ice cream maker takes over a warehouse on Big Blue’s former campus.

Kemps, which is owned by the Dairy Farmers of America cooperative, recently filed for a number of building permits for a “warehouse fit-up” of Building 205 at 2900 37th St. NW. It is one of the 34 buildings on the Rochester Technology Campus . That is the previous IBM campus.

The Rochester Technology Campus, owned by Los Angeles-based IRG, was previously known as the IBM campus. IRG paid $33.9 million to purchase the 490-acre campus from IBM in 2018.

When asked about how the warehouse will be used, DFA representatives replied that they had no information to share on the topic.

Rochester is the main site for Kemps’ ice cream production at the plant at 406 N. Broadway Ave. About 166 people work there.

Kemps, which is owned by the Dairy Farmers of America cooperative, recently filed for a number of building permits for a “warehouse fit-up” of Building 205 at 2900 37th St. NW. It is one of the 34 on the Rochester Technology Campus. That is the previous IBM campus.

Jeff Kiger / Post Bulletin

It is unclear if Kemps is leasing all of the space in Building 205, which is not connected to the main collection of buildings on the campus. It is located on the far west side of the campus. The 194,092-square-foot building features warehouse space, loading docks, offices and a mezzanine.

Kemps reduced its Rochester footprint in 2020 , when a milk processing facility at 700 1st Ave. SE that it shared with AMPI closed. However, ice cream remains a hot commodity

In 2019, Kemps said it could produce 86,000 units of ice cream, yogurt or frozen novelties a day, or 40 million units a year. The milk churned to ice cream comes from dairies located within 200 miles of the plant.

The ice cream facility’s history in Rochester dates back to the founding of the Parkin Ice Cream Co. of Rochester in 1911. Kemps Ice Cream Co. of Minneapolis was founded in 1914. Kemps was sold to Crescent Creamery in 1924.

Marigold Dairies of Rochester was founded in 1928 when W.R. Cammack, son of Crescent Creamery co-founder along with two former officers with the Vander Bie Ice Cream Co. of St. Paul, purchased Parkin Ice Cream.

Kemps, Crescent Creamery and Marigold joined forces in 1961. In 1968, the Dutch company NV Wessanen Koninklijke Fabrieken bought Marigold Foods. National Dairy Holdings then purchased Marigold in 2001, and it was renamed as Kemps in 2002.

In 2004, HP Hood purchased Kemps and then sold it to DFA in 2011.

Jeff Kiger tracks business action in Rochester and southeastern Minnesota every day in "Heard on the Street." Send tips to or via Twitter to @whereskiger . You can call him at 507-285-7798.

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