The role of the IT professional is often multi-faceted and varied, but ultimately one characteristic that ties us all together is our ability to solve problems. We’re always looking at the people, processes, and technology to address issues, support progress, and grow the business.
Now that we are working with gen-AI, the ability of IT to solve problems for the business, for our co-workers, and customers has never been greater. As such, gen-AI signifies a shift in the perception of IT professionals from technology stewards to stewards of positive change.
With a simple prompt, an IT pro can fix long-standing business problems more quickly and easily than ever, whether that means pulling data for a board meeting where critical decisions will be made or instantly or knitting applications together to enable the delivery of new products and services. If being a data-oriented problem solver was a skill before, AI has made it a superpower.
Facing The Fears And ‘AI-nxiety’
When the first generative AI programs started producing code, many within the technology world were – understandably – a little nervous about what this might mean for their jobs, not least as the tools continue to develop and mature. This “AI-nxiety” is of course not exclusive to IT – but foreboding predictions about the state of our industry in the not-too-distant future have hit the headlines in recent months and caused considerable concern.
But should we as IT professionals be worried – or, as the optimist in me is inclined to say – is generative AI a great opportunity for IT leaders to drive our field and our businesses forward?
The reality is probably somewhere in between.
In the short term, IT professionals will likely see their jobs have more importance than ever, as their businesses look to them to help create the data ecosystems and delivery models necessary for the successful implementation of generative AI (gen AI). Indeed, the input of IT teams in the governance, design, and practical implementation of gen-AI will be critical, as any organization looking to stay ahead of the curve is trying to use gen-AI to problem-solve more efficiently while avoiding the creation of unknown business risks.
Transforming The Business Landscape with Generative AI
Interestingly, SnapLogic recently released its “State of Data and Analytics Australia and New Zealand 2023” report in partnership with Corinium, exploring the current challenges, opportunities, and emerging trends as AI continues to transform the business landscape.
The results open many opportunities for organizations to rethink the impact of how AI is reshaping the landscape:
- High Demand for Expertise: 86% of respondents reported a notable increase in the demand for data and analytics expertise, indicating a sustained need for skilled professionals in the field.
- AI Reshaping the Landscape: AI emerges as a transformative force, with 89% of data leaders expecting a reduction in full-time hours within their organizations due to AI adoption. An overwhelming 90% believe that AI will drive the single greatest change in their data strategy over the next three to five years.
- Collaboration with Cybersecurity: 98% of participants underscored the importance of closer collaboration between data leaders and cybersecurity teams, emphasizing the need to safeguard data in an increasingly digital landscape.
- CEO Alignment: Only 6% of respondents report to their organization’s CEO, highlighting the limited direct connection between data and analytics leaders and top-level executives.
- Cloud Data Warehouses on the Rise: The report reveals that 92% of respondents are utilizing cloud data warehouses across multiple business functions, reflecting a growing reliance on cloud infrastructure for data management.
In the longer term, the impact of gen-AI on the IT person will likely be one of evolution rather than replacement. I believe that gen-AI is in many ways simultaneously the most underhyped and overhyped technology today: why? Because there is unfortunately a widespread lack of concrete factual knowledge about how these systems operate and will operate within the broader media and tech community.
This has resulted in unfounded speculation and catastrophizing that is unhelpful and damaging to the potential of these technologies. The reality is that the way that AI and machine learning function are so different, compared to the core technologies that most people are used to, that there’s a lot of unfounded hyperbole rooted in misunderstanding.
There’s a quote often attributed to Socrates that says: “I know only one thing: that I know nothing”. I think that this can speak to a lot of the misconceptions around AI at the moment. We are barely scratching the surface of real-life applications of gen-AI technology. We know very little. Yes, some generative models are spookily accurate in their responses to both general and specific inputs, but can they really replace skilled humans? Definitely not right now.
How Businesses Can Move from AI-Curious to AI-Ready
Generative AI And Smarter Integration
Generative AI is projected to have a profound impact on global business, with McKinsey estimating it could “add the equivalent of $4.4 trillion annually” through improvement of customer interactions, automation of business processes, conversational business intelligence, and IT acceleration via code generation. Unfortunately, companies seeking to capitalize on generative AI face prohibitive obstacles.
McKinsey cites a lack of available AI skills, the accuracy of results, and concerns about privacy and security as possible barriers to generative AI adoption in enterprises. SnapLogic plans to eliminate those obstacles.
SnapLogic recently unveiled GenAI Builder, the world’s first no-code generative AI application development product for enterprise applications and services. Uniquely compatible with both legacy mainframe data, modern databases, and APIs, GenAI Builder leverages conversational AI to transform and simplify customer, employee, and partner digital experiences.
As the latest addition to SnapLogic’s AI suite, GenAI Builder allows organizations to integrate AI with enterprise data to securely enhance the efficiency, accuracy, and personalization of data for every enterprise employee. This applies to multiple types of data, whether in the cloud or on-prem, and can be applied to critical use cases from customer support automation, data analysis and reporting, contract and document review, and personalized marketing. GenAI builder puts the power of LLMs and the scale of AI, where it matters most; in the hands of every enterprise employee.
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Take It From The Tale Of The Tractor And The Farmer
Most of us are familiar with the adage of the tractor and the farmer. The invention of the tractor didn’t replace the farmer, farmers just learned to drive tractors. The wisdom gained over centuries of craft and decades for each farmer was enhanced by the abilities that tractors provided. With that in mind, AI won’t replace the IT department, rather we will learn to be drivers of AI. To take the analogy a bit further, most tractors are guided by GPS today which farmers use to ensure they are as efficient and as optimized as possible. It’s this continued cycle of innovation, augmenting our job roles and making our lives easier and more efficient that we can expect to see with AI.
On the other hand, when we try and predict the AI space in five, or ten years down the line we don’t know enough to accurately predict its applications.
Yes, it will address problems we know about now, but what about the potential applications we don’t know about?
Going further, what if generative models can suggest solutions to problems we haven’t even identified even though they are in our midst?
Why IT Leads the Way
So, should we be worried about the future? Well, as IT professionals we are in a unique position to lead from the front – to partner with AI in individual contexts and guide its utilization and further development in business and beyond. The decisions we make and the problems we solve will define the AI space in the future.
IT staff are on the frontlines of what is undoubtedly a technological revolution and it’s our job to steer the ship, guide our businesses and our colleagues, and solve difficult problems for our customers.
For that reason, I urge IT colleagues to treat generative AI like a potential partner, not a competitor and not to be worried about a dystopian future or swayed by the hyperbole.
IT teams are competing among other business units to lead generative AI initiatives, and there is an opportunity like never before for IT teams to deliver on the promise of information and imagination at work, supported by and delivered by digital technology.
