GenAI could massively change industry and employment. The World Economic Forum’s Future of Jobs Report concludes: ‘While AI is being increasingly adopted by organizations worldwide, 49% of those surveyed… anticipate AI to be a catalyst for job creation, while 23% also expect it to drive job displacement.”
Similarly, according to a McKinsey report, generative AI could help automate the work taking 70% of employees’ time. The same report finds GenAI’s potential value to the world’s economy to be $4.4 trillion annually. Yet the fear persists that GenAI could take jobs away rather than add them. The truth, however, is that GenAI and humans must work together, particularly in digital operations – where the complexity and accuracy required is beyond what humans alone can manage.
This can be seen in the widespread adoption of GenAI in development teams. A Sonatype survey of 800 developers found 97% of DevOps and SecOps personnel are using GenAI. The survey found 45% of SecOps engineering leads are using GenAI, with 31% of DevOps teams adopting the technology. However, the study also found 74% reported feeling pressured to use GenAI despite security risks posed by the early-stage technology. This finding underscores the need for humans to guide GenAI as it develops, to inform it with intuition and experience.
It also shows that AI will complicate an already complex technology stack. This will support faster outputs but require more human management to keep digital operations online and effective using expertise and judgement. Legacy tech architectures also need investment. According to Deloitte, the average IT department invests over half of its technology budget on maintaining business operations, and only 19% on innovation. The IT patchwork plagues enterprises and there’s a critical need for skilled, knowledgeable software engineers and incident responders. If AI can be deployed correctly it could alleviate critical downtime. According to IDC, more than 53% of organizations say an hour of downtime on a revenue generating service costs a minimum of $100,000.
Yet without the data intelligence provided by AI, organizations will struggle to achieve operational maturity and resilience. AI can enable noise reduction, incident response and faster mean time to resolution (MTTR). When combined with human intuition, GenAI will bolster IT and customer success, with process automation fulfilling a critical role. Working in partnership with AI, IT teams can address traditionally siloed networks and efficiency barriers. And only through automation can engineering teams rapidly maintain uptime and quality of service and control data access, giving them time back to innovate.
To achieve this balance, organisations must utilise human skills and prepare teams for the AI era. These skills include investigation and analysis in fault finding, and reverse engineering. Therefore, engineers need programming capabilities and facilities with common architectures, with the skills to serve them. Appropriate skills can be acquired through various sources, including the online learning platform Coursera who partners with the likes of Google and the University of Washington to provide courses in AI proficiency.
Chief Information Officer at PagerDuty.
Combining human and AI skills
Education suited for GenAI includes proficiency in prompt engineering. This is learning how to ask the right questions to extract the most meaningful responses from AI, and the emerging profession can command £300k salaries. The skills required for this role are distinctly human. Prompt engineers must collaborate with cross-disciplinary teams, fulfilling consulting and quality control roles. They must also analyze and report on the data returned by the AI and establish meaningful metrics to measure the behaviors and performance of AI platforms.
There is a growing need for skills pertaining to new areas in natural language processing, machine learning, data engineering, data visualization and strategic data analysis. Graduates with interdisciplinary tech and soft skills may best suit AI. Such skills are cited by the University of Leeds who advocate communication, emotional intelligence, curiosity and communication, alongside the technical requirements of their Artificial Intelligence MSc, incorporating robotics, data mining and text analytics, machine learning and deep learning. The breadth of technical and human skills here shows how versatile IT teams must become. According to Karim Lakhani, Professor at Harvard Business School who specializes in workplace technology: “AI is not going to replace humans, but humans with AI are going to replace humans without AI. This is definitely the case for generative AI.”
Future-proofing the business with the right skills and hiring
Managing tech talent through AI’s impact and transformation will mean embracing the human skills which GenAI cannot replicate. These include interpersonal communication, empathy, teamwork and particularly creativity. For even if GenAI replicates creativity, it will never be accepted as a visceral response to the human condition. Would you be moved by sunflowers painted by an AI to the tune of $40m? Would a customer respond best to a human response or a chatbot?
The shared human experience is the fabric of every successful enterprise. This extends to IT teams, where engineers need programming skills, an intuitive facility with common architectures, and the individual and collective experience to solve incidents.
Communication, collaboration and innovation will also help CIOs/CTOs find and retain the talent to work alongside GenAI. This means offering a work environment that allows employees to do their best work, whether in the office or elsewhere. Leaders must also ensure the pipeline of new talent is more representative of society if responders are to solve diverse challenges for diverse customers.
Tech leaders must ask themselves how they want the industry to evolve. Will it be one of siloed technologies, diminishing skills and stretched IT teams? Or one where even more qualified human IT teams and responders use AI and automation to remedy digital incidents? It’s time for AI and humans to work together, and it’s time to build resilience by investing in long-lasting operational maturity. AI offers ways to support teams and technology stacks to minimize downtime and this will be essential for organizations to scale into the future.
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