How AI is disrupting the IT industry

Growing up in a family of engineers meant learning to take things apart and put them back together at a young age. This early start led me to excel at taking complex topics and conveying them in terms that resonate with people, opening a world of career paths. Leveraging these skills has led me through the ranks from inside sales, regional sales, national and international sales, to leadership and strategy responsibilities I currently oversee. Along the way I benefited from a rare opportunity to transition to a market analyst within an industry leading research firm, working with the key vendors on product and go to market strategy.

Behind great companies there is always great leadership, it’s a necessity for sustained growth. The main reason I chose to join ClickShare was because of the leadership I saw from our CEO, Charles Beauduin. During our first meeting, prior to ever considering joining ClickShare, Charles joined a meeting between myself and ClickShare leadership, and during the meeting he left a lasting impression. Throughout our interaction, Charles didn’t comport himself as the most important person in-room, but rather as a visionary who was motivated by the team outcome instead of his own agenda. When we moved locations, Charles recognized the value of the meeting and made sure those of us that needed to speak were the focus, to the extent he stepped in to serve those of us at the table. This style of ‘lead by example’ was so refreshing to see, and stayed with me for well over a year until the opportunity came to join the ClickShare team. I didn’t hesitate to join ClickShare, knowing the company’s leadership is decidedly different from most technology companies.

Being extraverted, curiosity and perseverance are the three character traits that are most instrumental to my success. My extraverted side is a crucial part of my identity and is also pivotal for my professional career. I’m always willing to share ideas and I’m never afraid to speak up which has created quite some new opportunities on my career path. In general people describe me as outward facing, engaging and very comfortable to voice opinions and ideas.

My curiosity and my eagerness to learn and ask questions brings me to new places, helps me to meet new people and explore new experiences. Having a healthy sense of curiosity perfectly aligns with my interest in international business. I do love to travel, explore how organizations work in an international context and how cultural differences make contacts fascinating. I’m careful not to take a position of a predetermined outcome, but to always be open to new ideas.

Never let fear stop you from doing anything. I’m not fearless, but I do not want to give up or give in. I might fail, but I’m always willing to give it a shot. And this has brought me many new experiences, technologies and insights in my professional life as well.

AI is disrupting the way the IT industry looks at the future of hybrid meetings. Through the data AI shares, IT leaders can determine the best setup for a conference or meeting based on what people want to do, while also ensuring a positive user interaction. AI has the potential to create a meaningful workplace, which helps our bottom line as our goal is to create a hybrid-meeting experience with the user in mind.

AI has been implemented for years already, from audio algorithms that can filter out dynamic noises (dogs barking, typing) to video algorithms that can focus on a presenter as they move throughout a room. More recently LLM (large language model) AI algorithms are being incorporated into meeting rooms through integrations with unified communications and collaboration (UCC) platforms like Microsoft Teams and Copilot.

These newer models are leveraging multiple types of AI to attribute who’s speaking on the call when multiple speakers are in the same room, transcription apps with translation capabilities for record keeping, and advanced capabilities for prioritization and meeting summaries. All these applications are currently being adopted across the world, but still in the early days of realizing the potential.

These advancements create many opportunities for a solution like ClickShare, where creating a great in-room experience is our top priority. Thinking towards the future, the ability to walk into a room and seamlessly dive into deep strategy and product discussions within a few seconds is only a couple years from being reality. Through AI technologies, a simple prompt could yield a fully articulated, complex process — such as preparing a SWOT (strengths, weaknesses, opportunities, and threats) analysis or product roadmap — without employees spending hours preparing slides.

AI isn’t new to the IT industry as it has become an integral part of analysing vast amounts of data, recognizing patterns and making complex business decisions. But AI technology such as Microsoft Co-Pilot has made the most significant impact in the IT industry when it comes to creating the ultimate in-room experience. For instance, IT managers that want to maximize AI platforms into their existing software can incorporate AI with Microsoft to identify failure points, how much is going on, and make decisions.

The hype around AI is recent, but those in product circles have been leveraging the tech for a decade, if not more. These models were far simpler, but they opened the door to what we’re now seeing in the market. The potential of AI has been discussed and explored for years, but the moment we started to see predictive analytics I began to realize there would be a revolution. With LLM AI in its renaissance, the most disruptive and innovative applications are just now coming into focus, and the in-room experience of employees is poised to take a huge step forward in the coming years.

Within ClickShare we are constantly exploring both how we adopt AI based tools internally, as well as how we incorporate them into our products. From these investigations, there is clearly a new skill set emerging in the workforce, and it is tied to prioritization. Employees that lean into AI tools and can identify when best to leverage them are at a clear advantage over those that continue to leverage manual processes to complete work. This gap is already growing and will only continue on an exponential track, it is vital that employees and management thoughtfully engage and determine what processes are safe to automate and which still require manual oversight. Furthermore, the lack of clarity around IP (Internet Protocol) is especially dangerous currently, as many employees leverage ‘free’ tools (outside corporate policy) to complete work, accidentally exposing information to the world without understanding the implications.

Training is the biggest challenge in upskilling for an AI-centric future. For instance, what tools to use, when to use them and when not to use them. These complex issues are evolving regularly, which means the workforce needs frequent updates on what is being used, and what workflows are ‘safe’ to accelerate with AI based tools.

Beyond standard training, there also needs to be training around why not to use AI tools that are not onboarded by the company. With offerings like ChatGPT’s copilot and Microsoft’s copilot sharing similar offerings, it makes it even tougher for employees to understand what is and isn’t acceptable practice. Many companies are playing with fire by not having clear standards.

There are a few ethical considerations AI introduces to the IT industry, including AI bias, privacy and security, public versus private LLMs, and the perception of the technology. AI bias is the top ethical consideration in the IT industry. Privacy and security, such as shadow issues, are also a massive risk. For instance, AI can have access to sensitive information, so there is a threat to intellectual property.

Public LLMs can be dangerous when dealing with NDA information, whereas private LLMs lack actual data privacy. The perception that technology is more accurate than humans, like how a company weighs a human response versus an AI generated response also poses challenges around whose opinion carries more weight, especially when the models being used are still prone to inaccuracies.