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How many of us can claim to have built a neural network? “Probably less than 1%” was Copilot’s unhelpful answer when we asked, but we suspect that Joseph George, General Manager of IT Solutions Group at GoTo, is closer to one in a million.
“I went to graduate school eager to specialise in AI and ML [machine learning],” he told us. “Unfortunately, AI computing capacity and big data processing in the early nineties just weren’t advanced enough yet to take off and study funding was limited – so, I ended up majoring in software engineering.”
But that’s good news for GoTo, famously the company behind GoToMyPC, where Joseph is now responsible for defining and optimising the portfolio’s business strategy. Prior to GoTo, he led product management for the IT Operations Management portfolio at BMC Software, which achieved ten-fold SaaS growth during his tenure.
It’s also good news for anyone reading this interview, as it means that Joseph can combine those years of experience – including time at startups and large corporations – with in-depth insight into what AI and ML can actually do for your business.
For example, we asked Joseph how educational institutions should adapt their IT curriculums to prepare students. “Unsurprisingly, the immediate priority and challenge is honing fundamental understanding of how to apply emerging tech, especially AI,” he said.
But he also flagged the need for ensuring students – our future IT professionals – to learn how to work well with our machine friends. They need, Joseph said, to elevate “their abilities in areas such as critical reasoning and creative or innovative thinking. In effect, sharpening their human edge.”
The best way to sharpen your human edge, you ask? Simple: sit down, grab a cup of tea, and read our full interview with Joseph.
Greater use of advanced technology will raise the bar for both efficiency and productivity across sectors. Many businesses are now reaching a vital transitional point where their experiments with artificial intelligence have started moving out of labs and pilots and into real-world production and operations. As this practical application of tech continues to evolve, AI tools will begin to make a real difference to everyday IT processes and, by extension, how teams function.
The adoption of intelligent agents and assistants is poised for significant near-term growth. Ongoing developments in machine learning (ML) and composite AI are persistently refining large language models by combining them with reasoning tools and resulting in improved cost economics. Consequently, generative tools will gain increased reliability and scope to emulate natural human communication, which will see them becoming mainstream staples in IT support and blurring the lines between man and machine, including potentially directly fielding more user queries.
In industry terms, this shift will fuel a focus on collaborative innovation, where firms increasingly harness tech to complement the skills of their human employees.
Meanwhile, handing basic issues to AI tools will empower IT experts to work smarter – giving them back time to proactively address intricate problems, instead of putting out one fire after another. Even in the event of reactive response, access to tech that can easily aggregate and analyse vast volumes of telemetry signals across systems will still help to hugely speed up problem resolution.
Technological progress was already moving quickly but this pace has been radically accelerated by recent leaps forward in AI. From the security perspective, the era of hyper-speed development has created a constantly escalating arms race. As bad actors use the latest sophisticated tech to mask their identity and break through defence layers, IT leaders face the need to find even more advanced ways of detecting and fighting these attacks.
The top priority for IT teams will therefore be enhancing their tech stacks by establishing robust protocols for anticipating and neutralising threats. The good news is that AI can also act as an asset to increase the resilience and efficiency of cybersecurity measures. For example, introducing AI-powered monitoring will help improve always-on protection, with intelligent tools continuously watching for anomalies and flagging any suspicious activity to help catch attackers before they can strike. Where incidents do occur, automated responses can also save precious time and minimise risks to internal systems.
Ethical considerations will centre on how to manage AI solutions responsibly. Regulations such as the European Union’s AI Act have set the ball rolling on defining broadly agreed standards and best practices, but actionable guidance is still relatively lacking — especially in the UK where AI-specific legislation has yet to arrive. For IT teams, this means the best short-term way forward is likely to lie with self-governance, which will include establishing clear guidelines for areas such as data usage and privacy protection, alongside strict multi-factor authentication to ensure secure data access and use.
IT is integral to keeping businesses running, with teams configuring and constantly maintaining the systems and solutions employees need to do their jobs in almost every industry. Given predictions that global digital transformation spending is set to exceed $3 trillion in the next two years, it’s also clear IT will remain paramount as more companies embrace emerging tech to sustain their competitive position.
What’s on the horizon for remote operations is slightly less certain. Yet while there are questions about the future of work, the growing call for direct human connection will likely continue in concert with varied iterations of remote models, including hybrid approaches. As a result, agile tech stacks will remain crucial for facilitating robust company operations and communications.
From the IT team standpoint, one core element of that will include harnessing tools that enable multi-modal interactions so employees can work effectively together wherever they’re located – giving them the choice of connecting using video calling, integrated chat tools such as Slack, or joining office-based conferences and virtual training sessions from home. In tandem, there will be a persistent requirement for robust security and helpdesk tools to support and safeguard workers as they switch between a host of networks and devices.
Unsurprisingly, the immediate priority and challenge is honing fundamental understanding of how to apply emerging tech, especially AI. According to recent studies, nearly seven in ten UK IT leaders expect an upsurge in demand for generative AI and similar innovations by 2027, yet around the same number also say a shortage of skills and expertise is the main factor holding their AI initiatives back.
In the longer term, IT knowledge needs will go beyond basic AI use. Circling back to our discussion about machine-augmented efficiency, businesses are entering an era where smart solutions will soon shoulder a much greater array of tasks. As well as freeing IT specialists from time-consuming and repetitive processes, this change will create an expectation for them to provide additional value on top of the productivity boost automated tech brings, including elevating their abilities in areas such as critical reasoning and creative or innovative thinking. In effect, sharpening their human edge.
All of this points to a requirement for multi-faceted education. At the technical level, programmes must teach students about the dynamics of intelligent tools and their security risks, in addition to offering opportunities to put learnings into action. Equally, it will be just as critical to retain a focus on honing other soft skills that will allow the next generation of talent to work in harmony with their fellow humans and autonomous ‘colleagues’.
I am a lifelong tech enthusiast who has always been fascinated by the scope for intelligent tech to mimic how the human brain works. After building a neural network for an undergraduate project while studying computer science at university, I went to graduate school eager to specialise in AI and ML. Unfortunately, AI computing capacity and big data processing in the early nineties just weren’t advanced enough yet to take off and study funding was limited – so, I ended up majoring in software engineering.
Since then, however, I have come to appreciate the positive impacts of this early curve ball. Thanks to my diverted career plans, I was able to tread a mixed path that combined tech and business, which means I can move between different worlds. In my previous AIOps role, my expertise allowed me to contribute towards AI and ML product innovation. Following my shift into IT endpoint management and enterprise remote support, I have drawn on my tech insights and understanding of business operations to help drive effective product optimisation and delivery.
What I now find incredibly inspiring is watching the growing power of AI/ML to truly transform and help us solve problems more efficiently than ever before and, in many cases, enable us to tackle a whole new range of problems. I am excited about the possibilities ahead.
One that springs to mind is GoTo’s efforts to improve access to integrated tech for small and medium-sized businesses (SMBs), as well as the managed service providers (MSP) that cater to them.
We recognise that modern companies are quickly becoming overloaded with a disparate muddle of disjointed tools, with many using different tools for security monitoring, remote access, patch management, asset tracking and more. To address this problem, we are delivering a multi-tenant AI-enhanced unified endpoint management platform that will enable centralised oversight and coordination of IT activities – essentially giving MSPs and SMBs a simplified platform and set of integrated capabilities powered by AI.
However, as a company we have many initiatives on the go that are influencing the future of IT, making life easier for human agents and transforming the IT support landscape.
This includes features designed to provide enhanced real-time support that drive faster and more precise issue resolution, such as conversational tools agents can use to run plainly-worded queries and receive tailored recommendations. Additionally, advances in AI-driven scripting are also allowing agents to scale tech fixes by entering the detailers of user problems and generating automated scripts that can run on multiple devices simultaneously.
