The study, conducted among 1,800 AI decision makers surveyed across six countries and 4,200 employees from 14 countries, highlights that despite strong enthusiasm for AI, there is a clear disconnect between trust in the technology and its actual use in the workplace. While 85% of decision-makers express high interest in AI, the vast majority (82%) acknowledge they need to better understand how AI can improve workplace efficiency.

Read Next: Four Questions to Guide High-Impact Enterprise AI Integrations

AI Workplace Challenges

Additionally, although 54% of employees believe AI can improve their work and 54% feel confident in their ability to collaborate successfully with AI, there’s still a significant gap in actual adoption in regular use at work. Jabra’s data found this appears due to several perceived challenges and demographic considerations:

• 90% of employees wouldn’t trust AI for tasks that require creativity and innovation. This reluctance isn’t just about trust, it’s also about the satisfaction that comes from being personally involved in these more meaningful tasks.
• There’s a clear generational divide in AI adoption, with 47% of Millennials and 37% of Gen Z indicating they feel positive about AI versus only 15% of Boomers. Adoption wise, 28% of Millennials and Gen Z use AI day to day at work, versus just 15% of Boomers.
• AI decision-makers are relatively young – 58% are between the ages of 18 and 39 – and 71% are not from the IT department.

Paul Sephton, head of brand communications at Jabra, says, “We see many organizations eager to jump on the AI wave, but some are still dancing in the dark when it comes to effective implementation and meaningful use. As tools rapidly shift toward voice-driven input rather than text alone, it’s crucial for organizations to recognize how this evolution will change our interactions with AI and enhance productivity.”

He continues, “To avoid what we call ‘AI-washing’— simply jumping on the AI bandwagon — organizations must carefully evaluate the productivity gains that AI can offer and actively involve their employees in this journey. At Jabra, we believe in harnessing the power of AI not just to enhance productivity, but to foster a more connected and capable workforce, driving innovation and collaboration at every level.”

Another version of this article originally appeared on our sister-site Commercial Integrator on October 23, 2024. It has since been updated for My TechDecisions’ audience.

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As more large learning models (LLMs) are coming to market, you might find that your enterprise customers are asking how they can automate processes and drive efficiency with AI. While eager to inquire, enterprise decision-makers often hesitate to invest in generative AI for their business upon discovering the significant resources, security considerations, and operational changes required to deploy an effective generative AI tool. While trendy, AI adoption still carries a lot of uncertainty and risk.

AI and the AV Industry

The good news is that our industry is uniquely positioned to help in this new scenario. As a trusted resource and advisor for technology decisions, clients trust AV integrators to offer AI-powered solutions that are ready for prime time and have a meaningful impact. These four critical questions can help integrators and technology managers adapt their discovery phase to incorporate AI into their AV technology roadmap.

Q1. What are the strengths and limitations of AI?

In response to the increased demand, technology vendors have rushed to develop AI integrations for everything — from truncating transcripts into meeting minutes to brainstorming ideas beyond reality. However, integrators should recognize both the efficacy and limitations of AI in truly enhancing the end-user experience. While generative AI can do a lot in its current state, it’s still best suited as a support tool for enhancing and accelerating processes rather than completely overtaking operations end to end.

The key is to identify discrete tasks that AI can successfully handle. If a human must significantly revise an AI’s output to make it usable, AI will waste more time than it saves. Work with clients to establish clear operational guidelines and oversight for AI tools to avoid these limitation roadblocks. This includes defining responsibilities; establishing handoffs between AI and human operators; allocating maintenance resources and having reasonable expectations. Once these boundaries are established, integrators can introduce effective opportunities to accelerate tasks with AI.

Q2. How do the strengths of AI support the client’s goals?

Properly trained AI can extend enterprise bandwidth by accelerating mundane-yet-time-consuming tasks, like retrieving data to answer questions or inform project timelines; providing employee and customer support; and digesting information to guide brainstorming and decision-making. This kind of implementation improves existing information retrieval processes. AI can also automatically compile information from across sources or customize responses to align with user data permissions.

Once you understand the capabilities of AI, it’s time to bring them to your client. To understand how AI can best support their organization, work with them to understand their unique pain points. Remember, the goal is to improve efficiency in existing systems, not replace processes entirely with AI.

AI functions must align with the interests of the enterprise and the evolving processes, demands and expectations of the business. Deployments should complement and improve the existing employee experience. AI should work across devices and processes, offering a reliable and seamless user experience. If an AI application does not make the job easier for enterprise customers, it’s probably not ready for deployment.

Q3. What training resources are available?

When trained with the right data aggregations, AI assistants can produce qualitative and quantitative-driven outputs that help streamline employee experiences, audience engagement, and objective results that benefit an organization’s defined visual goals and output. That being said, an AI’s responses are only ever as accurate as its dataset. Before launching an AI implementation for an application like sales, customer service or troubleshooting support, a business should have solid and up-to-date documentation of its processes and internal knowledge.

While AI implementation can make operations easier, it’s not an effortless addition to a business model. Deloitte cites managing internal data and processes as one of the most reported obstacles in scaling AI. It is important to inform the client about the continuous investment required for AI and discuss how they plan to maintain it. Before deployment, the business should evaluate whether the AI solutions that client plan to adopt are maintainable. They should then develop a long-term support plan and appoint someone to oversee the ethics and accuracy of the AI system.

Finally, ensure your clients can deliver on processes continuously after deployment, even if their AI tool is down. Integrators can help customers identify reliable, intuitive foundational AI tools that will support their business best, but setting realistic expectations that no AI tool will be free of error or downtime is the key to effective process management and planning.

Q4. What data is acceptable to share?

Data security is top of mind for enterprises, and while the benefits of AI are worth discussing, it’s crucial to educate clients about the potential risks linked with AI.

One risk is the “black box” paradox: the inner workings of AI systems are obscure to humans — this lack of transparency may pose challenges and lead to unforeseen consequences as AI evolves. That being said, sharing data and training is essential to successful AI implementation. Integrators must educate their clients to ensure they understand the risk. This will help clients make more informed decisions regarding adopting and implementing AI technologies.

Security is also a discussion point when evaluating whether an AI tool will operate on premises or in the cloud. On-premises solutions offer several benefits, including that data never leaves the local area network. This is especially important for businesses that deal with highly sensitive data.

Additionally, on-premises solutions offer firewall protection and integration with internal contact/user data, which enables AI to learn identity and permissions. Finally, on-premises solutions provide access to highly secure employee-facing AI chat with responses derived from proprietary company data.

On the other hand, cloud-based solutions offer flexibility, high scalability and accessibility for distributed workforces. However, clients have less control over data distribution than an on-prem solution. Data and encryption keys are stored with third-party providers. This means that if there is downtime, clients may be unable to access their data.

While each option has its benefits and drawbacks, integrators should advocate for establishing a solid security protocol and best practices before sharing data with an AI assistant.

Concluding Thoughts

While the AI landscape fluctuates, these four questions can guide integrators in evaluating and recommending the right AI investments to meet enterprise customer demands. While some clients might be ready for AI, other organizations might need more preparation before taking the leap. Emphasizing genuine operational enhancements over fleeting trends is paramount, guiding clients toward integrations that yield enduring advantages.

Another version of this article originally appeared on our sister-site Commercial Integrator on March 19, 2024. It has since been updated for My TechDecisions’ audience.

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The White House Center for Science and Technology Policy defined the five core principles that underpin the Blueprint for an AI Bill of Rights. In July 2023, several large technology companies including Google and Meta convened at the White House to announce voluntary commitments advancing the safe, secure, and transparent development of AI. The latest order sets out to define standards for safety and security, advance equity and civil rights, promote innovation and competition, and ensure transparency to protect consumers. This sweeping order also promises to foster strong international collaboration to ensure the same principles guide global AI development. Let’s delve into the key areas and explore five main takeaways.

1) Defines New Standards for AI Safety & Security

The executive order requires that companies developing the most powerful AI algorithms notify the government when they are training these models and share critical safety test data with the U.S. government. This will apply to models that may pose national security, economic, public health, and safety risks. The National Institute of Standards and Technology (NIST) will develop rigorous standards to ensure that AI systems are secure and trustworthy prior to their public release. The order also builds on the Biden-Harris Administration Artificial Intelligence Cyber Challenge (AIxCC) with a cybersecurity program that encourages the adoption of AI tools to flag and mitigate vulnerabilities in critical software.

2) Emphasizes Privacy & Data Protection

The Biden Administration’s order is developing programs that will evaluate and develop best practices for federal agencies to protect data privacy for Americans. This program will fund the creation of a Research Coordination Network which will collaborate closely with the National Science Foundation to encourage widespread adoption of cutting-edge privacy technologies by federal agencies. This order also requires that federal agencies be provided with stronger guidance on how they collect and use commercially available information in order to mitigate the risks posed by AI.

3) Advances Equity & Civil Rights

The Blueprint for an AI Bill of Rights identifies algorithmic discrimination as an emerging area that undermines equality and civil rights. Guidelines and best practices will be developed to help ensure that AI is used responsibly in the criminal justice system, benefits programs, federal contractors, landlords, and in workplaces. Federal law enforcement agencies will be equipped with the knowledge, skills, and tools to properly investigate and prosecute civil rights violations that involve the use of AI.

4) Advocates for Patients, Workers & Consumers

Society enjoys real benefits from AI applications — including improved healthcare research and delivery, greater productivity, and more personalized experiences in several settings. However, AI brings with it increased workplace surveillance, bias, and potential for discrimination in medical, employment, consumer, and educational settings. The White House Executive Order on Artificial Intelligence benefits workers by defining guiding principles and best practices to ensure employers do not misuse AI to exploit or discriminate against workers. It also establishes a budget to ensure that AI is used effectively and ethically for the development of lifesaving healthcare treatments and to correct healthcare practices.

5) Promotes American Leadership in AI Innovation & Fosters Competition

This order, along with others issued in recent years, fosters breakthrough innovation by authorizing pilot programs, grants and education opportunities. It also emphasizes the need for international, multi-disciplinary collaboration to ensure that the future of AI is safe and trustworthy everywhere. To this end, the State and Commerce Departments will lead international efforts to institute effective frameworks and accelerate the creation of crucial international AI standards that will mitigate risks while still allowing people to take advantage of AI’s many benefits.

The executive order’s standards, best practices, and principles lay a strong foundation for developing responsible, equitable AI systems. The U.S., in collaboration with international partners, aims to ensure that AI is trustworthy, upholds individual rights, and its fullest potential is maximized to support critical global initiatives. AI is still in its early stages, but this Bill marks an important milestone.

Jennifer Mullen, Emerging Technology Solutions at Keysight Technologies (KEYS)

The post 5 Things You Need to Know About the White House Executive Order on Artificial Intelligence appeared first on My TechDecisions.

For decades, writers and filmmakers have imagined dystopian futures where AI displaces and tries to destroy humanity. So, it’s understandable that people are apprehensive about generative AI’s foray into the workplace. It’s important to acknowledge AI’s transformative effect on workplaces, industries, economies and everyday life in ways we’re just starting to envision.

Even before ChatGPT came on the scene, researchers projected AI would displace 85 million jobs by 2025, but that same study also predicted 97 million new jobs will be created. Organizations that embrace and develop AI, provide incentives for employees to use it and create a human-centric culture where AI helps employees succeed at work will win the future.

As CTO of a team that recently launched a successful AI product for the global employer of record market, I’m optimistic — not only about the value of the technology but also for the employees whose knowledge and expertise AI will augment. Here’s a closer look at how employees and AI complement each other’s strengths and can work together to create business value within a human-centric company culture.

AI Should Augment Human Capabilities Rather Than Replace People

To address the elephant in the room, AI won’t replace human knowledge workers. It requires our insight into what’s happening in the real world to grow and learn to accomplish new tasks. According to some studies, approximately 90% of content online is predicted to be AI generated by 2026, i.e., synthetic data. In some scenarios, synthetic data is useful for training specific models. In fact, a 2021 leveraging synthetic data to refine AI-powered fraud detection tools.

But past a certain point, synthetic data can corrupt large language models due to LLMs depending on unique, creative insight related to real-life events, systems and trends to produce reliable answers. Models like ChatGPT may curate and repurpose existing content, but they also rely on human knowledge and creative thinking that transcends linear reasoning. For example, if companies are trying to hire, recruit and pay international talent, turn to AI for the latest HR best practices, which often change in response to new legislation and emerging trends, they’d need to use an AI model that incorporates human expertise to ensure accurate answers.

Some of the most exciting applications of generative AI are solutions that combine proprietary business expertise with LLM platforms to create a generative AI chat interface. This type of knowledge base can expedite delivery of information to internal and external customers and become a more valuable business asset over time as it learns and improves. But that’s only the case if company leaders think of employees not just as people who help administer the technology but as partners in a sociotechnical system, where people and AI work together, each making contributions to generate value.

Redefining Employee Roles in AI-Powered Industries

The best way to create a system where interactions between humans and technology create value is to build AI solutions in collaboration with employees, not as a separate project to replace them. This is especially important in industries that offer expertise and knowledge as their primary product.

A productive AI-human partnership will require new ways of thinking about how to deliver knowledge to customers. For example, in some jobs, employees apply expertise by responding to emails, submitting helpdesk tickets or collaborating with customers on phone calls. A new role for those employees might be analyzing emerging trends, writing content and training models, bringing the same expertise to solve customer problems in a novel way.

To develop AI solutions that augment employee expertise and knowledge, technology leaders will first need unfettered access to company data — including information that might be difficult to reach due to the use of legacy systems. They’ll also require AI-specific talent to help build out the solution, a blend of expertise from the software engineering and data science disciplines. That’s a commodity already in short supply, so finding people with the right skills should be a priority for an AI project.

Equally as important, building AI solutions will require incentives across the workforce to fine-tune the generative AI solution after launch. As the model ingests more and more information, it learns and becomes more adept at solving problems. Employers who bring more people into the conversation with AI will create additional value by providing multiple perspectives. So, if a customer has a question, the AI chat interface can provide an initial answer that can later be refined by human partners to create a solution that includes well thought-out strategies.

Building a Human-Centric Culture

So how can companies create a generative loop where humans and AI work together to constantly improve output? My AI project team created a chat interface that automates some of the mundane and time-consuming aspects of our knowledge workers’ jobs, and this has proved to be a powerful motivator for employees to keep engaging with the system. It frees staff from tedious tasks and gives them more time to focus on higher level work. That benefit answers the “what’s in it for me?” question that employees naturally ask themselves.

Other real-world examples of ROI from our AI project include employees getting instant answers to questions, when before they used to have to wait hours or days for a subject matter expert to weigh in so they could resolve an issue for a client. Another internal user called the chat interface a gamechanger because it can instantly access data across multiple systems that a person would have to laboriously assemble by consulting several different applications and datasets.

If you can create an architecture that seamlessly accesses data companywide and put together an innovation team that’s encouraged to experiment and explore new possibilities with emerging AI technology, you can build a solution that adds value immediately. And if you operate within an environment where people are adaptable and motivated to access AI to fulfill your company’s mission, you can leverage that human-centric culture to transform the business.

Every business will adapt in its own unique way, but being transparent about how AI will affect roles, encouraging employees to embrace change and instituting a more collaborative approach are essential across the board. Ready or not, generative AI will continue to transform the way companies operate, and an AI-driven business transformation, that leverages human capital, can offer exciting opportunities for businesses to serve customers better and gain a competitive edge.

Duri Chitayat is CTO of Safeguard Global

The post Leading the Evolution Towards Human-Centric AI Work Cultures appeared first on My TechDecisions.

Tech industry employment experienced a net increase of 12,922 new positions, the largest monthly gain since April 2023, CompTIA’s analysis of U.S. Bureau of Labor Statistics (BLS) Jobs Report data reveals. Jobs were added in four of the five primary sub-sectors, led by technology services and software development (+8,500) and cloud infrastructure and related positions (+4,400). Tech manufacturing led by semiconductors also had a solid month (+1,600).

Technology occupations throughout the economy declined by 79,000 positions last month, according to CompTIA.’s report. The unemployment rate for tech occupations increased to 2.3%. In comparison the national unemployment rate stands at 3.7%.

Tech Employment Remains Optimistic 

“Tech employment remains on solid footing,” says Tim Herbert, chief research officer at CompTIA. “Despite the ongoing pattern of mixed signals in the labor market tracking data, the optimistic outlook continues to hold.”

Job postings for tech occupations also fell back. Active job postings for tech positions totaled nearly 364,000, including 142,295 newly added by employers in December, according to the CompTIA report. Employer hiring for artificial intelligence job roles and specialized skills continues to exceed the 10% threshold as a percentage of all tech job postings.

Industries with the largest volumes of tech job postings included professional, scientific and technical services; administrative and support services; and manufacturing. Among metropolitan markets, Washington, New York, Dallas, Chicago and Los Angeles had the most tech job openings. Meanwhile, Pittsburgh and Providence recorded modest month over month gains in postings.

The CompTIA Tech Jobs Report is available at comptia.org/content/tech-jobs-report.

Another version of this article originally appeared on our sister-site Commercial Integrator on January 5, 2024. It has since been updated for My TechDecisions’ audience.

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The Exciting Part of AI

Seeing images and sceneries get constructed in front of our eyes and resulting in flawless visuals is breath taking. Receiving on-point responses to our various inquiries and engaging in a constructive conversation with a web application is fascinating. Viewing personalities recorded on video having a discussion they never had in real life is jaw dropping. This is where exciting starts. But it is not what AI can only do. It can do real work making us more productive. It can make supply chain decisions. It can make medical diagnosis. It can make personalized curriculums for students based on their individual capabilities.

At the core of it, AI is possible because of two things: an advanced algorithm and data—lots of data. AI algorithms differ from what we’ve traditionally been accustomed to in previous technology innovations. They do not rely on if/then/else logic. There is no human-inferred logic at all. It is left to the machine to draw decisions based on its deep learning with the help of neural networks and data. AI feeds on data. The more the data, the better AI is in developing synopsis and characterization.

AI has become very good in making decisions on content development, customer insight, production processes and even medical diagnosis. It is one thing for AI to do what we do. It another thing for AI to do it better than us. AI now has lower error rates than those of a human. That’s where excitement turns into fear.

The Frightening Part of AI

The fear from AI falls into three camps. The first is around the bias generated by AI. AI reflects on what it learns from data. It is hard to ensure that data is inclusive of all situations. If it is a loan approval AI, is it influenced by demographics or environmental conditions? There is no standard validation of AI data. Thus, there is a concern that although AI can be precise based on the data feeding it, it can be biased. And if there is probability of bias, how can we trust its objective reasoning when it comes to sensitive areas.

The second fear from AI is loss of jobs. If AI is destined to be as good and better than a human in resolving issues, accomplishing tasks, and making decisions, it is only time before AI replaces people in the workforce. Forecasts range from 10% to 70% loss of jobs by 2030. We haven’t been good at forecasting the impact of previous innovations; nonetheless, there will be change. It is not necessarily all bad. There will be opportunities with roles never existed before, like prompt engineering. Humans can adapt to changes. The only difference here is that it is happening at an astounding speed.

Living with AI makes the third fear. AI as we know it today does not yet fit its theoretical definition of mimicking how a human brain works in thinking, rationalizing and directing behavior. People can do their taxes, paint a canvas, engage in jury duty and hold a conversation on ancient literature. We may not do all of them with expertise, but we can cross-learn and think about multitude of topics. In contrast, AI today is deep and narrow. AI image generator cannot review financial statements. But then again, it is unlikely we have a judge who is also a surgeon. We don’t know if, or when, AI capabilities will eventually converge with that of humans. But if they do, what will become of our purpose? Even with the current state of multiple specialized AI solutions where each can generate efficiencies in respective areas, will a business with a single owner employing AI to serve business operations be a state we are willing to accept and live with?

The Curiosity to Keep AI Going

We’ve been curious about AI since 2011 when IBM Watson beat Jeopardy champion and earlier in 1997 when IBM Deep Blue supercomputer beat the world’s champion in chess. The fears may be big, but the curiosity is bigger. What is else is possible? And how much is possible?

Neither of the fears above has a strong rebuttal, so they are all valid. AI can redefine who we are and what we do, especially when AI starts generating and managing new AI without any human guidance. Time magazine’s End of Humanity cover and an AI Pause request letter from AI enthusiasts make these fears more real. But it is all hypothetical. We don’t know what we don’t know. That’s why it is hard to pause now. We are all curious to know. Curiosity will continue to drive us to learn, experiment and innovate. The result can be something we never dreamed of before. Will AI help us travel in time? Will we gain the knowledge to explore outer galaxies at the speed of light because of the extra artificial neural power we will have? Will this become our new purpose and identity rather than a job title?

What to Do Today

As an individual, it is important to get comfortable with AI. If not to use, then to know well. We will all be touched by it in the near future, if not already, one way or another. We should ask questions—not out of fear but out of curiosity. And we should actively participate in developing it and making it better as it pertains to our domain and our expertise.

A business or an organization should engage in AI adoption to advance operations efficiency and decisioning precision. But in parallel, it should equally focus on social responsibility. Social responsibility is a mandatory track for the diffusion and evolution of AI. Understanding anticipated impacts and actively working to transition societies to a workable future state is the responsibility of every business benefiting from AI. The work around social responsibility is lagging, hence the fear. For it to catch up, AI advancement does not have to slow down or pause. We just have to turbo charge social awareness and practical solutioning. That goes beyond setting limiting laws and protocols. Ironically, AI may be option to help set its own social guardrail.

In practice, an organization needs to find its AI opportunities. After understanding that AI is not a blanket solution across the chain of operations, targeting efficiencies in a particular area (acquisition, production, fulfillment) is where progress and success can be achieved. From there, a respective model or algorithm is identified and secured. The marketplace has sufficient models to choose from with simple setup. Third party data can be leveraged for the AI, but if an organization wants or depends on its distinctive customer base insights, then increased efforts of first party data collection, curation, cleansing, storing, and analyzing is necessary. This will empower their AI solution to provide tailored decisions and directions supporting their unique efficiency and growth trajectory.

Raghid El-Yafouri is the Technology and Digital Transformation Consultant at Bottle Rocket Studios.

The post What is It About AI That Brings Excitement, Fear and Curiosity All at Once? appeared first on My TechDecisions.

Artificial Intelligence (AI) is quickly becoming a mainstay in our everyday lives. Whether it be text-to-image generators like DALL-E or language processing tools like ChatGPT, sophisticated AI tools are revolutionizing the way we work.

That’s especially true in the hybrid workplace, where organizations are searching for new ways to bridge the gap between distributed employees. Given this challenge, it’s no wonder that videoconferencing has emerged as AI’s next step in revolutionizing how we live and work.

Let’s explore AI’s role in videoconferencing and how its latest innovations are improving the meeting experience.

The Rise of AI-Powered Videoconferencing

It should come as no surprise that demand for videoconferencing apps has grown exponentially since the start of the pandemic in spring 2020. Without question, virtual meetings are the bedrock of hybrid work, enabling organizations to seamlessly connect and collaborate across a distributed workforce.

This uptick in demand runs parallel with the emergence of several new competitors in the videoconferencing market. In turn, vendors have been compelled to improve their services by releasing feature-rich additions to their existing applications.

AI technologies have also advanced in leaps and bounds over the same period. In fact, reports show that AI adoption is 2.5 times greater now than it was in 2017. The market is projected to skyrocket twentyfold by 2030 to nearly $2 trillion.

Now, the two worlds are converging. Leading platforms are weaving AI capabilities into their videoconferencing tools to enhance the meeting experience for maximum productivity and performance.

Four Ways AI Can Transform the Videoconferencing Experience

Gone are the days when organizing, running and managing your virtual meetings was a clunky, cumbersome endeavor. Thanks to AI’s advantages, videoconferencing platforms are empowering organizations to kick up their internal and external meetings several notches.

Here are four of the most impactful ways AI-driven solutions can improve the meeting experience.

#1 Natural Language Processing (NLP)

Natural language processing is a branch of AI that enables computers to understand text and spoken words in the same way a real person can. In other words, it’s about giving AI programs the power of conversational intelligence.

Modern videoconferencing tools are leveraging NLP across a host of innovative capabilities, including:

• Voice-to-text transcription: Using NLP, an AI-enabled platform can recognize and process complete sentences as they’re spoken during the meeting. This allows the system to automatically capture meeting notes, summarize conversations and generate searchable transcripts. When machine learning tools are incorporated, videoconferencing platforms can even identify who is speaking during the meeting.
• Real-time translation: Global enterprises may be holding internal or external meetings that stretch beyond borders and include attendees who speak different languages. With AI, the meeting software can give everyone an equitable experience by automatically translating live audio into the language of any user’s choice.
• Closed captions: Likewise, NLP capabilities can analyze audio and generate closed captions to make the meeting experience more inclusive for all participants.
• Noise removal: From cars and pets to housemates and more, there’s no telling what sounds might suddenly disrupt and derail a meeting. Machine learning can be used to train AI to identify and remove those noises before they’re picked up. For hybrid teams, this is especially useful, as automatic background noise removal and acoustic fencing filters out distractions in different locations to keep meetings running smoothly.
• Sentiment analysis: Consider the customer experience use case for videoconferencing: contact center agents working on resolutions in real-time. One major benefit for agents is AI’s ability to understand sentiment and tone during a conversation. Programs can analyze a speaker’s voice to uncover pain points and frustrations during the interaction. This allows managers to evaluate both customer experience and agent performance for future improvements.

#2 Conversational AI

Although they’re also built on NLP, conversational AI programs stand on their own. In simple terms, conversational AI refers to platforms that can chat and interact with users. That said, their capabilities stretch far beyond simple back-and-forth communication.

For example, voice-based virtual assistants can be used to streamline meeting management. Users can simply speak to their endpoints and apps to kickstart a meeting, turn on their camera, capture important items and control the experience from start to finish.

Chatbots can also be asked to schedule follow-up meetings with attendees, assign action items, send automated reminders and more.

#3 Computer Vision (CV)

According to Aragon Research, computer vision will have the biggest impact on intelligent videoconferencing in the future. This type of AI uses algorithms to understand, analyze and reconstruct visual inputs from image or video data.

This has several innovative use cases for meetings:

• Optimized framing: CV can help participants stay in their cameras’ frame when presenting to colleagues and customers. By automatically tracking the speaker’s movements, the system keeps you centered in your video to eliminate unwanted distractions. In addition, multiple cameras in a room can now work together by switching cameras views to focus on the active speaker. The result? A cinematic video experience that follows the conversation from one speaker to the next.
• Adaptive tracking: For meetings with multiple speakers, CV programs can ensure everyone is equally represented on screen. During webinars, cameras can adaptively track speakers as they move across the room or auditorium stage, ensuring that they’re always in everyone’s view.
• Immersive presentations: Virtual presentations are challenging in hybrid settings. CV allows presenters to deliver more immersive content by automatically screen sharing in front of presentation materials.
• Meeting zones: AI will soon use machine learning to automatically learn and frame your space based on predefined boundaries. This will ensure that distraction from passers-by are removed from the meeting in glass-walled rooms or open space.

#4 Productivity Analytics

People spend a lot of time in meetings these days. So, it’s important for organizations to ensure that time is well spent on value-added activities and core business processes. Fortunately, AI-powered solutions are helping businesses capture meeting data and leverage it to their advantage.

AI enhances data collection and offers users the power to evaluate key metrics. For example, platforms can record time spent on certain agenda items and activities, back-to-back meetings and other real-time insights that can be delivered directly to employees to help improve their productivity.

The Future of AI-Driven Videoconferencing

In truth, we are only scratching the surface when it comes to what AI can bring to the table. But, with the videoconferencing market expected to double by 2030, it’s safe to say that AI-powered meetings will be a major asset for years to come.

Robyn Rawlings is director of campaigns and content marketing at Webex by Cisco.

The post AI’s Revolutionary Impact on the Videoconferencing Experience appeared first on My TechDecisions.

In today’s hybrid-work environments, individuals work from a variety of spaces, and in nearly every workspace, noise and poor sound quality can negatively affect collaboration and productivity. A recent Equipping Your Employees for Hybrid Work study found that 85% of work-from-home users struggle with audio issues, whether it’s from background noise from other participants or poor sound quality through computer speakers. The same study found that hybrid workforces aren’t properly equipped with modern collaboration tools, such as quality headsets.

“Zone Wireless 2 is Logitech’s top-of-the-line headset for skilled professionals who need technology with a high degree of control, precision and innovation,” says Prakash Arunkundrum, chief operating officer at Logitech. “We built Zone Wireless 2 with advanced technology for uncompromising performance at a lower carbon footprint.”

Zone Wireless 2 Features

Per a statement, the headset notably allows the user to suppress ambient noise from the other person’s side of the call, even if that person is not wearing a noise-canceling headset. The Advanced Call Clarity feature, activated through Logi Tune, uses AI to separate the other caller’s voice from their background. Noise-canceling mics suppress distracting sounds and near conversations through advanced beamforming technology that captures the user’s voice, thus creating a two-way noise suppression system.

Hybrid Active Noise Cancellation (ANC)

Hybrid active noise cancellation (ANC) blocks out ambient noise around employee workspaces such as keyboard clicks, nearby talkers and HVAC noises; and transparency mode, which helps users stay aware of their surroundings while wearing the headset, the company states. Upon setup on Logi Tune, users can use the Personal EQ feature to customize the headset to fit their individual hearing range through a self-administered hearing test.

Bluetooth and Smart Enumeration

As professionals transition through different scenarios in their workday, they can stay connected with multipoint Bluetooth and smart enumeration. According to the company, the patent-pending feature solves the problem users often experience when they leave their computer, lose connection, then return to a setup that appears to be audio-connected but isn’t. Smart enumeration is the result of communication among headset, USB-C receiver and the operating system to intelligently switch between headset and computer audio without the user having to manually toggle among audio sources or remove a dongle, says Logitech.

Battery Life

To power up professional busy work schedules, Zone Wireless 2 provides up to 40 hours of battery life, with talk time and listening time varying based on whether ANC is on or off. A quick five-minute charge provides up to one hour of talk time, says Logitech.

The headset include breathable earcups, available in graphite, off-white and rose colorways to suit professionals’ personality and style. While enjoying immersive sound, style, and comfort, professionals can tap or swipe on the ear cup to control media and volume using smart touch controls or enable on-ear detection in Logi Tune to automatically play or pause media when wearing or removing the headset.

IT Management

According to Logitech, IT teams can deploy Zone Wireless 2 to their workforce — the headset is certified for Microsoft Teams with a microphone for open office, Zoom, Google Meet, Google Voice, and Fast Pair. Integration with Sync, Logitech’s device management platform, provides a secure and scalable approach to remotely manage Logitech devices. Sync allows IT admins to update firmware and troubleshoot Zone Wireless 2, whether the headset is used remotely or in the office, from a single, cloud-based interface.

Zone Wireless 2 Sustainability Features

Sustainability is core to every design decision from the moment raw materials are sourced to the end-of-life of Logitech’s products, says Logitech. Zone Wireless 2 is designed to give users the ability to extend the life of their device by including interchangeable earpads and a replaceable battery, keeping more headsets on heads and extending the life of the headset.

According to the company, the plastic parts in Zone Wireless 2 include 20% certified post-consumer recycled plastic to give a second life to end-of-life plastic from old consumer electronics, and the aluminum in Zone Wireless 2’s decoration ring and temple extension are made by a process that uses renewable energy instead of traditional fossil-fuel energy.

The paper packaging of Zone Wireless 2 comes from FSCTM-certified forests and other controlled sources. Logitech says it is committed to creating a climate positive world by actively working to reduce our carbon impact. Zone Wireless 2 is certified carbon neutral. The carbon impact of the product and packaging has been reduced to zero due to Logitech’s investment in carbon offsetting and removal projects.

Zone Wireless 2 Pricing & Availability

Per a statement, the Zone Wireless 2 is available globally on logitech.com and through authorized resellers. The suggested price for the headset is $299 USD. To purchase through retail channels, Zone 950 is available in the U.S. and Canada (graphite only).

Another version of this article originally appeared on our sister-site Commercial Integrator on October 16, 2023. It has since been updated for My TechDecisions’ audience.

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Technology has been a passion of mine for a long time, so I have personally found it fascinating to watch the variety of opinions and perspectives unfold as technologies mature. It has challenged my thinking and preconceptions, and I recognize that as a leader and a human I need to address them.

I’ve covered everything from fundamental ethics and whether it is good or bad, through to more specific considerations like ‘what do I want from AI?’, and therefore ‘what might others want from it?’.

Naturally, it’s been hotly debated by my colleagues. The leadership team is considering how today’s and tomorrow’s versions of AI should shape our own role in AI creation and adoption.

We already know that artificial intelligence for IT operations (AIOps) is poised to take advantage of the benefits. At Avantra, we’ve long evangelized the value of automation to offset risk, better utilize skill and boost productivity and innovation. But the debate that surrounds AI has helped us understand that our next phase of technical development must be underpinned with even greater pragmatism and responsibility.

The latest numbers I saw suggest that every day, 100 million people are experimenting with the likes of ChatGPT and other Large Language Models (LLM), such as Bard. Numbers like this highlight the popularity and allure that machines still have. Just like the washing machine, if it makes life easier, why would you not use it?

Download: ChatGPT and Generative AI in the Workplace

Proceeding with Caution

However, even though world renowned university colleges are condoning the use of conversational AI tools, leading experts are urging caution — legalities, politics, economics and ethics are top of the list of concerns.

It was eloquently summed up by The Future Life Institute, which is made up of over 1,000 experts, in an open letter asking the industry to pause AI development, or risk humanity and society. LLMs are learning so much so fast, that we, as a species, haven’t had time to truly process the long term impact. Ethics are at stake.

Taking Responsibility is Urgent

I think it’s a responsible challenge. As I said before the headlines have provoked my own thinking to evolve and prompted me to consider whether such a warning could, should or even will stop our own industry from forging on.

This is where I think the application of AI must be balanced against the dilemma. Take the example of producing project documentation or new product technical summaries. Is using ChatGPT to create the first draft irresponsible or a boon for productivity, freeing up time for innovation in other areas? Similarly, with the introduction of ‘copilot’ tools, like Microsoft assistant, people can increase their productivity and have more time for other things, even just going to the gym. I can see how it could make a sustainable argument for a four day week and happier colleagues.

Can Conversational AI Help Our Industry?

Of course, in my world, the real advantage of introducing ML and AI is the ability to help customers find answers to the problems they face. Using conversational AI to mine a database of known and defined errors other businesses have encountered — be that on SAP or Google — would help practitioners arrive at answers far sooner and avoid a degradation in productivity.

The process would augment the value of the intelligence we aggregate and own and, as it’s a trusted source, accelerate decision making and the time to resolution (TTR). No human can realistically (nor would they want to) hold in their brain all the common problem scenarios and fixes.

I’ve tried to do this in my professional career, and though possible, it is exhausting. That’s why I believe, applying conversational AI to the common challenges our customers face would help highly qualified and skilled humans validate and implement the decisions they take.

I’d advocate that automating the interrogation of vast knowledge banks makes complete sense, especially when it helps skilled people get on with doing what they do best — running, managing, and developing world class ERP.

I should be clear that I am wedded to the notion that it’s important the wider industry runs the AI race in tandem with the ethics that protect humanity. We must thoroughly understand the implications at every point in development and put in place the checks, balances and regulation to ensure the values we hold dear are protected and enhanced, not obliterated.

In the world of AIOps there is real value to its adoption not least to ensure mission critical systems related to food supply or energy stay online. We must therefore consider the broad view of AI technology as well as our narrower domain. Only with a balanced view and appreciation of the accountability we assume as leaders, can we make the right choices.

John Appleby leads Avantra as the Chief Executive Officer. Before Avantra John served as the Global Head of DDM/HANA Center of Excellence at SAP and as the Global Head of SAP HANA solutions at Bluefin Solutions, subsequently acquired by Mindtree. John is a recognized thought leader in the SAP market and was part of SAP’s Mentors Group. John holds an MA in computer science from the University of Cambridge.

The post Does Conversational AI Have A Role to Play in AIOps? appeared first on My TechDecisions.

On the platform side, Zoom’s big announcements included features like Zoom Docs, an AI-powered workspace for docs, wikis and work management. This is in addition to new Zoom AI Companion features such as the ability to generate ideas on a digital whiteboard and organization them into categories and expanded access to Zoom AI Companion for education and healthcare customers.

However, the company also made several announcements related to hybrid meetings at Zoomtopia, which is especially important to integrators that serve both residential and enterprise markets.

New Zoom Features for Hybrid Meetings

Following Zoomtopia, Zoom will begin rolling out name tags for each in-office meeting participant, so remote users will be able to identify people by name during the meeting and in meeting transcripts.

The company will also be adding a wayfinding feature next year, providing a map showing a route to the seat a hybrid worker reserved in the office.

In addition, Zoom will be rolling out new features next year for its virtual co-working tool Huddles, including “my office view,” which will help workers know when colleagues are in a virtual huddle or in the physical office along with their presence and location.

Zoom will also be rolling out this December Dynamic Layouts for Zoom Rooms, a feature designed to make it easier to follow a conversation between on-screen colleagues. Now available in beta, users will see video frames shift dynamically in real time as participants raise their hands or begin speaking so remote workers know here to focus their attention.

At Zoomtopia, Zoom also announced the general availability of Intelligent Director, a new feature designed to optimize the conference room experience for hybrid work, using multiple cameras to give every participant their own frame and best visual angle in Zoom Meetings. It supports up to three cameras with the ability to set it up for small, medium and large rooms.

Other hybrid meeting features include a new note-taking feature, improvements to continuous meeting chat, asynchronous video clips and a new scheduling tool.

Specific to AV teams, Zoom is rolling out later this year Pro AV for Zoom Rooms, a new tool for AV professionals to manage multiple physical and virtual audio and video streams. It features a wide range of hardware support and partners for cameras and controllers and is designed for AV experts integrating Zoom into large, custom events.

Zoom Partner Program Updates at Zoomtopia

The videoconferencing and collaboration provider also announced updates to the Zoom Up Partner Program while at Zoomtopia. This update adds three new levels to the partner program: Silver, Gold and Platinum. Partners can onboard to the Zoom Up program in just a few hours of training and move up to higher levels by demonstrating knowledge and skill of the Zoom portfolio.

Rewards re-tiered in accordance with the Zoom Up level achieved, the company says.

Zoom is also adding new offerings and resources, such as a partner customer success program, a partner support program, a new partner licensing program and more.

New Zoom Hardware

Meeting room hardware manufacturers have been helping integrators support their customers’ Zoom Room environments for many years, and many of those manufactures used Zoom’s event to announce new products, features and offerings of their own.

That includes Crestron, which announced Zoom certification for the Videobar 70 and intelligent video cameras and a new Zoom Phone Appliance and Scheduling Panel with Zoom Rooms software.

Meanwhile, HP and subsidiary Poly also announced several new offerings and products, including the Poly Studio Bundle, which the company says is designed to leverage the Zoom Rooms Intelligent Director feature by applying AI to create more equitable meeting experiences in large rooms. The bundle includes three Poly Studio E70 cameras, a Poly TC10 controller, and an HP Mini Conferencing PC.

In addition to the recently announced Poly Voyager Surround 85 UC Bluetooth headset, the company also announced two new HP webcams with 1080p resolution, automatic focus, lighting and color correction, two new wireless keyboards and a Bluetooth mouse.

Another version of this article originally appeared on our sister-site CEPro on October 10, 2023. It has since been updated for My TechDecisions’ audience.

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