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Obstacles and Opportunities of Democratizing AI for Organizations

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Obstacles and Opportunities of Democratizing AI for Organizations


Enterprise deployment of artificial intelligence (AI) is positioned for tremendous growth.

Artificial intelligence is set to change the business world by improving predictive analytics, sales forecasting, customer needs, process automation and security systems.

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Source: Everest Group

IBM’s Global AI Adoption Index revealed that a third of those surveyed will be investing in AI skills and solutions over the next 12 months. 

More expansive use of AI democratizes AI, providing access to insights to more people – technologists and non-technologists alike. The latter group might include people in leadership, sales, finance, human resources and operations. This is where AI will shine, empowering business teams to make AI-driven decisions.

Imagine: business teams do not have to know how to code or be schooled in the intricacies of AI’s backend. Instead, they will use AI like you and I use a mobile phone for efficiency (if we’re running late, we merely send a text notifying the other person), access information faster (if we’re in the grocery store and need a recipe, we look it up), make better decisions (GPS gives us the fastest route).

Just as mobile technology works without us understanding complex circuitry, algorithms or software, the democratization of AI across enterprises will be integrated in much the same way.

So, what will hold AI back and how will AI help enterprise companies gain traction?

3 Obstacles and Opportunities Organizations Face by Implementing Artificial Intelligence

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Artificial intelligence deployment approach | Source: IBM

Obstacle #1: Data in disarray. Data that does not provide a complete picture and single version of truth because of data silos and various data formats within an organization.

Opportunity: Employing a data fabric. Using a data fabric to help organizations use data more effectively and get the right data to users regardless of where it is stored. One significant advantage of a data fabric is that data governance rules may be automatically set for compliance.

Having one information structure to garner insights and analytics from, integrating security to protect sensitive data and establishing a framework for implementing trustworthy AI positions AI as part of the business strategy, not solely an IT strategy so that AI directly impacts business operations.

It all comes back to connecting data with business drivers and a data fabric helps accomplish this. It is what I call “point-to-point” thinking – knowing the business imperatives, business drivers, the different levels of raw data, who is consuming the data, who will have access to the data, and why the data is important in decision-making and then, the big payoff with AI, how it will elevate experiences: customer experience, workforce experience, supply chain experience, strategic partner experience, community experience. In “point-to-point” thinking we don’t hoard data, but share it – securely.

Obstacle #2: Varied skill levels. A lack of AI technical skills across the enterprise and a reliable, open platform to bring AI to more people.

Opportunity: Creating a bridge to AI for people within the enterprise. Palantir for IBM Cloud Pak for Data is one of the great innovations of our time because it doesn’t require coding skills. People in non-technical roles can go from raw data to data insights quickly using application templates (think of all the designs being produced with minimal design experience because of apps like Adobe Photoshop and Canva). This is truly the path to democratizing AI.

People can now use AI to make better decisions in real time and improve business outcomes. These teams include sales and marketing, manufacturing operations, campaign managers, branch managers, franchise operators, human resources, among others.

An example: a customer walks into their regional bank. The banking professional greets the customer, invites them to sit down and pulls up their profile. They see, not only account information, but a 360-degree view of the person sitting across from them. Through a data fabric, non-tabular visualizations gathered from previously siloed data originating from different systems provides an AI-infused perspective.

This might include two algorithmically recommended customer offers inspired by marketing analyst data and intelligent customer segmentation and campaign propensity scoring powered by Watson models.

Going further, feedback from the customer can then be entered and that data influences future offers because it goes right back into IBM’s data and AI platform. IBM Cloud Pak for Data, which helps to simplify data management and protect sensitive data by establishing a framework for implementing trustworthy AI.

Obstacle #3: Solving for the wrong “x.” In hundreds of conversations I’ve had with enterprise leaders over the years about AI, one common failure I see not identifying the right problem or identifying use cases that will yield high return from AI.

Opportunity: Clearly articulating the problem to be solved. With AI, we are talking about a machine making reasonable conclusions based on data. Better defining the problem is akin to asking better questions.

Imagine the difference if you were in a store and asked someone if they sold products. The question is too vague to expect a meaningful answer. Ask where the tomatoes are and you get a clear answer. Both are valid questions, but one is more focused. That’s how defining the problem should be (this is not just for AI purposes; I devote a lot of space in my book, Ascend Your Startup, to defining the customer problem because I believe building the wrong solutions plagues many companies)

Key Takeaways

How Artificial Intelligence Is Revolutionizing the Advertising Industry

In an interview with famed Mount Everest climber George Mallory, a reporter asked him why he wanted to climb the formidable mountain. His answer: “Because it’s there.” AI is very much the same thing. It has obstacles, yet it has the allure of opportunity and of making measurable progress.

Here are the big three takeaways for enterprise companies:

•  Use a data fabric. Information is powerful – and it exists! Don’t let siloed data and inconsistent data formats hold people back from making better decisions.

•  Give people what they need to succeed in their jobs. Tools such as low code/no code enable business users to rapidly leverage data and apply AI in their decision making. 

•  Go back to square one and define the problem. Solving for “x” without fully understanding “x” wastes precious time, causes unnecessary frustration and marginalizes the experience for everyone involved.

The Rise of AI

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Source: Statista

In a Forbes article on the topic of AI, author Manas Agrawal writes, “With rapid learning and adoption, AI is no longer a crystal ball technology but something that humans now interact with in nearly every sphere of life.”

In a very short time, we won’t be talking about AI adoption as people see it as part of doing business and part of making life more efficient. AI then will shift to being part of an enterprise’s business strategy, delivering value for non-technical people working in many different areas like customer experience, brand differentiation, HR, research and development, management and sales.

This is what the democratization of AI looks like at the crossroad of technology and humanity to improve outcomes for people leading successful enterprise businesses.



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Radware launches a spinoff of its cloud security business

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Cloud Computing News

Duncan is an award-winning editor with more than 20 years experience in journalism. Having launched his tech journalism career as editor of Arabian Computer News in Dubai, he has since edited an array of tech and digital marketing publications, including Computer Business Review, TechWeekEurope, Figaro Digital, Digit and Marketing Gazette.


Radware, a provider of cyber security and application delivery solutions, has revealed the spinoff of its Cloud Native Protector (CNP) business to form a new company called SkyHawk Security.

To accelerate Skyhawk Security’s development and growth opportunities, an affiliate of Tiger Global Management will make a $35 million strategic external investment, resulting in a valuation of $180 million. Tiger Global Management is a leading global technology investment firm focused on private and public companies in the internet, software, and financial technology sectors.

Skyhawk Security is a leader in cloud threat detection and protects dozens of the world’s leading organizations using its artificial intelligence and machine learning technologies. Its Cloud Native Protector provides comprehensive protection for workloads and applications hosted in public cloud environments. It uses a multi-layered approach that covers the overall security posture of the cloud and threats to individual workloads. Easy-to-deploy, the agentless solution identifies and prevents compliance violations, cloud security misconfigurations, excessive permissions, and malicious activity in the cloud.

“We recognize the growing opportunities in the public cloud security market and are planning to capitalize on them,” said Roy Zisapel, Radware’s president and CEO. “We look forward to partnering with Tiger Global Management to scale the business, unlock even more security value for customers, and position Skyhawk Security for long-term success.”

The spinoff, which adds to Radware’s recently announced strategic cloud services initiative, further demonstrates the company’s ongoing commitment to innovation. Skyhawk Security will have the ability to operate with even greater sales, marketing, and product focus as well as speed and flexibility. Current and new CNP customers will benefit from future product development efforts, while CNP services for existing customers will continue without interruption.

Radware does not expect the deal to materially affect operating results for the second quarter or full year of 2022.

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How Sports Organizations Are Using AR, VR and AI to Bring Fans to The Game

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How Sports Organizations Are Using AR, VR and AI to Bring Fans to The Game

AR, VR, and AI in sports are changing how fans experience and engage with their favorite games.

That’s why various organizations in the sports industry are leveraging these technologies to provide more personalized and immersive digital experiences.

How do you get a sports fan’s attention when there are so many other entertainment options? By using emerging technologies to create unforgettable experiences for them! Innovative organizations in the sports industry are integrating AR, VR and AI in sports marketing and fan engagement strategies. Read on to discover how these innovative technologies are being leveraged to enhance the game-day experience for sports fans.  

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AUGMENTED REALITY IN SPORTS

AR is computer-generated imagery (CGI) that superimposes digitally created visuals onto real-world environments. Common examples of AR include heads-up displays in cars, navigation apps and weather forecasts. AR has been around for decades, but only recently has it become widely available to consumers through mobile devices. One of the best ways sports organizations can use AR is to bring historical moments to life. This can help fans connect to the past in new ways, increase brand affinity and encourage them to visit stadiums to see these experiences in person. INDE has done just that, creating an augmented reality experience that lets fans meet their favorite players at the NFL Draft.

VIRTUAL REALITY IN SPORTS

VR is a computer-generated simulation of an artificial environment that lets you interact with that environment. You experience VR by wearing a headset that transports you to a computer-generated environment and lets you see, hear, smell, taste, and touch it as if you were actually there. VR can be especially impactful for sports because it lets fans experience something they would normally not be able to do. Fans can feel what it’s like to be a quarterback on the field, a skier in a race, a trapeze artist, or any other scenario they’d like. The VR experience is fully immersive, and the user is able to interact with the content using hand-held controllers. This enables users to move around and explore their virtual environment as if they were actually present in it.

ARTIFICIAL INTELLIGENCE IN SPORTS

Artificial intelligence is machine intelligence implemented in software or hardware and designed to complete tasks that humans usually do. AI tools can manage large amounts of data, identify patterns and make predictions based on that data. AI is already influencing all aspects of sports, from fan experience to talent management. Organizations are using AI to power better digital experiences for fans. They’re also using it to collect and analyze data about fan behavior and preferences, which helps organizers better understand what their customers want. AI is also changing the game on the field, with organizations using it to make better decisions in real time, improve training and manage player health. Much of this AI is powered by machine learning, which is a type of AI that uses data to train computer systems to learn without being programmed. Machine learning is the reason why AI is able to evolve and get better over time — it allows AI systems to adjust and improve based on new data.

MERGING THE REAL AND VIRTUAL

VR and AR are both incredible technologies that offer unique benefits. VR, for example, is an immersive experience that allows you to fully imagine and explore another virtual space. AR, on the other hand, is a technology that allows you to see and interact with the real world while also being able to see digital content superimposed on top of it. VR and AR are both rapidly evolving and can have a significant impact on sports marketing. By using both technologies, brands and sporting organizations can create experiences that bridge the real and virtual. This can help sports marketers create more engaging experiences that truly immerse their customers in the game.

Technologies like AR, VR and AI in sports are making it possible for fans to enjoy their favorite games in entirely new ways. AR, for example, can help sports lovers experience historical moments, VR lets them immerse themselves in the game, and AI brings them more personalized and immersive digital experiences. The best part is that sports fans can also use these technologies to interact with one another and feel even more connected. 

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The Dark Side of Wearable Technology

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The Dark Side of Wearable Technology

Wearable technology, such as smartwatches, fitness trackers, and other devices, has become increasingly popular in recent years.

These devices can provide a wealth of information about our health and activity levels, and can even help us stay connected with our loved ones. However, there is also a dark side to wearable technology, including issues related to privacy, security, and addiction. In this article, we will explore some of the darker aspects of wearable technology and the potential risks associated with these devices.

1. Privacy Concerns

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Source: Deloitte

Wearable technology can collect and transmit a significant amount of personal data, including location, health information, and more. This data is often shared with third parties, such as app developers and advertisers, and can be used to track and target users with personalized advertising. Additionally, many wearable devices lack robust security measures, making them vulnerable to hacking and data breaches. This can put users’ personal information at risk and expose them to identity theft and other cybercrimes.

2. Security Risks

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Source: MDPI

Wearable technology can also pose security risks, both to the individual user and to organizations. For example, hackers can use wearable devices to gain access to sensitive information, such as financial data or personal contacts, and use this information for malicious purposes. Additionally, wearable technology can be used to gain unauthorized access to secure areas, such as buildings or computer systems, which can be a major concern for organizations and governments.

3. Addiction Issues

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Source: Very Well Mind

The constant connectivity and access to information provided by wearable technology can also lead to addiction. The constant notifications and the ability to check social media, emails and other apps can create a constant need to check the device, leading to addiction-like symptoms such as anxiety, insomnia and depression.

4. Health Risks

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Source: RSSB 

Wearable technology can also pose health risks, such as skin irritation and allergic reactions caused by the materials used in the device. Additionally, the constant use of wearable technology can lead to poor posture and repetitive stress injuries, such as carpal tunnel syndrome. It is important for users to be aware of these risks and to take steps to protect their health, such as taking regular breaks from using the device and practicing good ergonomics.

Conclusion

Wearable technology has the potential to be a powerful tool for improving our health, fitness, and overall well-being. However, it is important to be aware of the darker aspects of wearable technology and the potential risks associated with these devices. By understanding the privacy, security, addiction, and health risks associated with wearable technology, users can take steps to protect themselves and their personal information. Additionally, by being aware of these risks, organizations can take steps to protect their employees and customers from the potential negative effects of wearable technology.

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