An Interview With Chad Silverstein
Businesses can stay on top of their complex IT environments. Often consisting of legacy deployments, third party apps, hybrid cloud set ups, there is so much data spread across network that data silos and blind spots are inevitable. Left unexposed these lead to poor user experience and outages. AI — and AIOps in particular — simplifies network monitoring and maintenance, while never taking away control from IT teams.
In today’s tech-driven world, artificial intelligence has become a key enabler of business success. But the question remains — how can businesses effectively harness AI to address their unique challenges while staying true to ethical principles? To explore this topic further, we are interviewing Richard Tworek.
Richard Tworek is the Chief Technology Officer at Riverbed Technology where he leads the product management, engineering, and data science teams in building and enhancing the Riverbed unified observability portfolio.
Thank you so much for joining us in this interview series. Before we dive into our discussion, our readers would love to “get to know you” a bit better. Can you share with us the backstory about what brought you to your specific career path in AI?
I’ve had a passion for technology since I was crawling. Accelerating the story, it went from building robots as a child to writing code for the US Navy. I was a submarine commander and alongside operating the subs, I wrote code that helped it to operate more effectively. Since then, I’ve held several business and technology leadership roles before joining Riverbed in early 2021.
My interest in Machine Learning (ML) has been there since the 80s. The really stark difference between then and now is the horsepower that’s available to support deployments. It was a real limiting factor back then, meaning development took time and technology predictions were measured in years, if not decades. The speed of change now is so rapid, spurred on by evolving GPUs and the consumer introduction of OpenAI’s ChatGPT, that we’re looking at 6-month intervals.
At Riverbed, we’ve had 20 years of applying ML, and that expertise combined with the available processing power means it’s an exciting time for us. We’re supporting customers with tools that are developed with AI as standard and they’re experiencing real business change through greater monitoring and analysis of networks.
Can you share the most interesting story that happened to you since you started working with artificial intelligence?
As I’ve been developing our AI capabilities at Riverbed what really became apparent to me was the need for precision about what IT teams really care about. AI is so broad and can bring benefits to so many different aspects, but individuals only really focus on a handful. For example, showing an IT Manager AI’s impact on overall business performance may help them to see the bigger picture, but it’s not showing them how AI can solve the everyday issues they face. By focusing on a few areas of the network, they can really see how AI can help address the challenges.
More specifically, Artificial Intelligence for IT Operations (AIOps), which can support monitoring and fixing network issues, are really beginning to deliver for organisations. Empowering IT teams to manage complex IT environments, AIOps can enhance user and customer experiences. In fact, Global Credit Union told us that they ran 13,000 automations over 90 days, saving 20 minutes per incident. This equates to $1.5 million savings in people resources that can now be used elsewhere.
You are a successful leader in the AI space. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?
- Being hands off. I provide the north star but then I task my teams to come back with ideas. Our people possess so much knowledge and I trust that this will shine through in their thinking. If leaders are too hands-on, it can stifle freedom of thought.
- I encourage my team to act like a start-up. Achieving goals, particularly when it comes to technology development, takes a lot of experimentation and teams need to be free of the restrictions that can come as businesses grow and establish.
- I always keep an open mind about how AI can be used internally at Riverbed. I’m constantly engaging with my team about how we can adopt it to improve their experience. We’ve used it to enhance how we build software, provide more detailed documentation and enhance quality assurance, for example.
Let’s jump to the primary focus of our interview. Can you share a specific example of how you or your organization used AI to solve a major business challenge? What was the problem, and how did AI help address it?
Riverbed has such a rich heritage of customers and it’s been fascinating to be a part of their journeys.
We understand our focus — which is supercharging enterprise IT teams through helping to analyze performance data of applications, networks and endpoint behavior — and we stick to that niche. That expertise and passion, alongside the rapid speed of technology, means we’re consistently asking ourselves how AI can solve our customers’ business problems and, with many of them being early technology adopters, they are receptive to our suggestions and become ‘lighthouse customers’ — guiding the way for everyone else.
Our recent launch addresses three major challenges enterprise IT teams are facing. Firstly, they need to consolidate IT tools with many deploying 20–30 to keep networks running. Secondly, AI deployment needs to beat the hype and actually deliver real ROI. Thirdly, they need to work at scale to support all data initiatives across the organization. The launch includes new technology incorporating Generative, Predictive, and Agentic AI, unified AI agents and Open Telemetry — all of which support organisations in turning networks into richer sources of information for business growth.
Our customers are really seeing the benefits of early adoption. For example, a large global financial institution expects to save $32 million in 5 years through Riverbed automations that eliminate the need for remote log-in to users systems during help desk calls. While a Risk & Human Capital Leader was able to improve Teams performance for 10,000 users throughs automated detection and remediations or Teams issues. It also saved IT 2,500 hours monthly and improved user productivity. All of that time and money saved is now being invested elsewhere in the business.
What are some of the common misconceptions you’ve encountered about using AI in business? How do you address those misconceptions?
Some of the misconceptions are around a perceived loss of control. When asking technology to take on more responsibility and automation, that can come with a concern that humans will no longer have any input. Business and IT leaders still want to ‘push the button’ and really understand what the intended outcome of an AI activity is so they feel in control.
Driverless cars provide an interesting example of the balance between automation and control. Autonomous cars exist but they still have a steering wheel and we’re some way off them having no windows and effectively being a box that transports you. The confidence in the technology isn’t there yet. So, it’s a matter of sophistication and what you’re asking the AI to do. Asking it to pick you up from a parking spot where you can see the vehicle clearly the entire way is very different to it driving you miles away without any windows.
At Riverbed, we anticipated these concerns which is why we developed our tools so humans are always in control. For example, we built break points into solutions where human approval is needed to proceed. We also take everything in small steps. If you lose the customers trust around AI use it’s’ very difficult to get it back — would you still feel comfortable if your autonomous car crashed? So we build slow and steady with them.
Hallucinations are another challenge. How can business leaders ensure AI outputs are actually correct? We add parameters to our solutions so that each output is scrutinized and tested every step of the way.
In your opinion, what is the most significant way AI can make a positive impact on businesses today?
AI’s ability to boost productivity is its biggest asset. It won’t replace humans as there’s no lack of business problems to address, but it will upskill people to get better results. For example, the same group of people can now write more code or solve more complex issues driving business growth. AI effectively helps them to become ‘smarter’.
Based on your experience and research, can you please share “5 Ways AI Can Solve Complex Business Problems”? These can be strategies, insights, or tools that companies can use to make the most of AI in addressing their challenges.
- Businesses can stay on top of their complex IT environments. Often consisting of legacy deployments, third party apps, hybrid cloud set ups, there is so much data spread across network that data silos and blind spots are inevitable. Left unexposed these lead to poor user experience and outages. AI — and AIOps in particular — simplifies network monitoring and maintenance, while never taking away control from IT teams.
- Run analytics on business data that wasn’t possible before. You can now find that needle in the haystack in a vast volume of data quickly, fueling faster, more informed decision making.
- Sort through mountains of data to find trends that would otherwise be difficult to visualize. There is so much information available from historical to forecasts and AI allows businesses to connect the dots.
- Accelerate the important but time-consuming activities. Whether it’s developing contracts or writing code, AI can provide a much faster route to outcomes.
- Deliver a better user experience. Companies that can’t keep up with evolving user demands will soon see customers and employees leaving to competitors using AI as the experience on offer is much greater.
How can smaller businesses or startups, with limited budgets, begin to integrate AI into their operations effectively?
“I’ve founded three businesses and it’s a phenomenal time for start-ups when you consider the technology available. So many exciting new companies are being born out of technology, with so much AI support around coding, network configuration and other areas that have typically required complex technical understanding.
“For more established small businesses, take advantage of AI to support areas that would be typically expensive to operate. Network diagnostics, for instance, traditionally might require big expert teams or expensive third-party partners, but AIOps can autonomously flag and, in some cases, rectify network issues. Ultimately, this means some of the money that would’ve been spent on keeping networks operational can be diverted to sales and other tangible business-growing activities.”
What advice would you give to business leaders who are hesitant to adopt AI because of fear, misconceptions, or lack of understanding?
AI doesn’t need to be that scary. There are so many guardrails in place that AI needs to be directed and controlled meaning humans are always in charge. But for any that feel hesitant, they can start by consuming it in small chunks. Get ChatGPT to rewrite CVs or suggest a recipe. Once business leaders increase familiarity with the simple tools, they can start to see how larger tools can introduce new efficiencies and activities in their companies.
Additionally, they should view AI as a growth driver, something that 58% of business leaders agree will be the case by 2027, according to a Riverbed survey. Tools support employees through allowing them to do their jobs more effectively so they can focus on activity that will boost growth. To gauge employees’ confidence with AI, business leaders need to listen to their people. Different generations are more comfortable with technology so seek advice from across the company to understand how AI is and can be used further.
In your opinion, how will AI continue to shape the business world over the next 5–10 years? Are there any trends or emerging innovations you’re particularly excited about?
Technology is moving so quickly that looking 5 to 10 years in the future will just fuel wild predictions. We’re now on 6-month intervals with a consistent stream of technological launches that push the boundaries of what’s possible.
In the short- to medium-term, agentic AI will be a big focus that brings true business benefits. AI agents, backed by Model Context Protocol (MCP) will enable the building of wide-reaching ecosystems that enhance collaboration and the resolution of issues. MCP is an approach that allows Large Language Models (LLM) to communicate, ensuring a seamless flow of data. This means businesses can deploy a large number of AI agents which are all individually configured to autonomously handle specific activity, such as monitoring and remediation certain aspects within business networks, with the confidence that they will also work in tandem.
How do you think the use of AI to solve business problems influences relationships with customers, employees, and the broader community?
Ultimately all stakeholders want to drive the most from relationships. AI that can deliver ROI and work at scale can solve business problems faster, delivering a better user experience. Businesses have traditionally needed to build big teams to keep customers, partners and employees happy, but AI is reducing that burden by equipping individuals with expanded capabilities.
You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people through AI, what would that be? You never know what your idea can trigger. 🙂
I wouldn’t be starting the movement, but I am a big advocate of agri-tech. AI that enables the better use of land, decreases crop waste through greater measurement and just-in-time planning and developing greener energy sources can go a long way in addressing many of the world’s issues.
How can our readers further follow you online?
I’m quite active on LinkedIn so do connect with me on there and to learn more about Riverbed’s AIOps solutions, visit us here.
This was great. Thank you so much for the time you spent sharing with us.
About the Interviewer: Chad Silverstein is a seasoned entrepreneur with 25+ years of experience as a Founder and CEO. While attending Ohio State University, he launched his first company, Choice Recovery, Inc., a nationally recognized healthcare collection agency — twice ranked the #1 workplace in Ohio. In 2013, he founded [re]start, helping thousands of people find meaningful career opportunities. After selling both companies, Chad shifted his focus to his true passion — leadership. Today, he coaches founders and CEOs at Built to Lead, advises Authority Magazine’s Thought Leader Incubator.
Richard Tworek Of Riverbed On How Artificial Intelligence Can Solve Business Problems was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.