The Future of IT in the Age of AI

To kick off 2025, I originally planned to write about the future of IT in general.  But I quickly surrendered to the fact that, at this moment in time, the future of IT really mostly boils down to two letters: AI.  Since we know AI is going to continue to advance and extend its tentacles into everything, the question is not “will it happen”, but rather “what will it look like?”  So that’s what I’m going to explore here.  Focusing on internal business operations, I’m going to lay out some AI predictions, trends, and bits of practical advice.

WHERE IS AI TAKING US?

I’ll start with the heavy stuff: be prepared for AI to drastically transform the very nature of business over the next 10 years or so.  By 2035, certain aspects of the way businesses operate might not even be recognizable to our 2025 selves.  I believe today’s business leaders need to assume that a very drastic AI transformation will play out, and then work backwards from there to develop at least a rough roadmap for your business.  If the drastic scenario doesn’t play out?  Great; you’re ahead of the game.  But if it does play out and you have not prepared?

So… let’s paint a picture of what this extreme AI-powered business scenario might look like ten years down the road.  Put on your time travel helmets – you are now in the year 2035:

• AI PREVALENCE IN 2035: The rush to embrace AI was universal.  In most industries, competitive survival required it. AI-powered businesses are now the norm.  Autonomous AI agents handle a significant portion of day-to-day operations with virtually no human interaction; these agents communicate directly with each other and carry out a wide variety of decisions and tasks behind the scenes.
  
  
• WORKFORCE IN 2035: Starting back in the early 2020’s, AI steadily improved its ability to enhance employee productivity in new and better ways.  Its problem-solving became increasingly sophisticated.  But early on, employees also realized that AI’s ability to mimic – and ultimately displace – humans could pose a threat to their livelihood.  And they were right.  Permanent employees have been significantly displaced by AI systems and freelance specialists.  Now, AI even handles most business decisions!  This has resulted in sharp reductions in human leadership teams.  Of course many roles are still primarily performed by humans.  But the hottest skill sets are now in the development and management of technology systems.  And almost every employee, no matter their role, has had to reskill, upskill, and become much more AI-literate.

• WORKER ENHANCEMENTS IN 2035:  Most employees have an AI assistant.  Wearable technology for employees is now commonplace, including things like VR glasses, controller gloves, and exoskeletons.  But, more significantly, some companies have now begun to test computer chip implants in human bodies.  These implants are designed to augment an employee’s cognitive capabilities related to their work tasks.  This practice has raised serious ethical controversy because it will ultimately put those who are unwilling or unable to do it at a disadvantage in the workforce.
  
  
• ORG STRUCTURE IN 2035: Most businesses now have a Chief AI Officer (CAIO or CAI) or a Chief Technology Operations Officer (CTOO).  It’s not common anymore to run IT and Operations as separate functions.  They are more likely to be combined within a single “AI” or “Technology Operations” department, which is often seen as the most important group in the organization.

• SPEND & REVENUE IN 2035: By 2030, the majority of companies were spending more on AI technology than on human employees in most industries. And around the same time, AI started generating more revenue than human employees. AI is now the largest driver of growth.
  
  
• COMPETITION IN 2035: AI technologies have evened the playing field, favoring small businesses whose capabilities have been enhanced to rival those of larger companies and whose agility allows them to adapt more quickly.

OK – back in 2025 (snaps fingers).  Considering that the future imagined above is even a possibility, there sure are a lot of implications for IT in the intervening years, aren’t there?

AI’S EFFECT ON BUSINESS STRATEGY TODAY

AI has become a game changer in strategic planning because of its ramifications for so many different areas of the business.  Not only will it profoundly reshape both the technical and operational sides of the organization, it will ultimately blur the distinction between them.

• IT is undergoing a “re-branding” – the increased focus on AI is, by necessity, putting IT front and center in conversations around business strategy.  Today’s IT function needs to be (and should be recognized as) a strategic business partner, an agent of change, and a driver of transformation.  IT can no longer just support strategies, it has to originate strategies.
  
• Companies are planning around both AI’s benefits and its threats – including threats to their business model. 
• IT roadmaps are being shortened – commercial AI offerings are fast to value and have low barriers to entry.  The pace of change will keep accelerating, and as a result it’s harder to plan forward with accuracy.  IT roadmaps are now commonly 12-24 months instead of 3 years, revised more frequently, with more flexibility and less detail the further out they go.
  
• Budgets are being adjusted – as we enter 2025, organizations are reducing spend in other core tech areas (such as cloud, security, and IoT) to direct more budget toward AI.
  
• Org structures are changing – ideally, someone at the senior leadership level needs to own corporate AI strategy.  Companies need to consider creating a formal CAIO (or similar) role, and consider what it would look like to create an internal “Tech Operations” (or similar) team that merges your IT and Operations functions and has a deep focus on business systems.
  
• Job roles are changing (or going away) – beyond using generative AI to augment day-to-day tasks and interact with customers, the concept of the “digital worker” is becoming a real thing. Salesforce is already pitching its Agentforce as “digital labor”.  Today, AI efficiencies in sales, marketing, and customer support are already proving their ROI.  By 2026, audio-based AI agents may outpace text-based AI agents.  In 2025 more companies will need to seriously reckon with AI actually replacing jobs. 

A TOP-DOWN APPROACH TO AI

AI initiatives fall into two main categories: 

1. Customer-facing: building AI into your products
2. Internal: building AI into your business operations 

If number 1 applies to your company, you’re already doing it (and that’s not the focus of this article).

Number 2 applies to everyone.  Some companies are already quite far along in their “internal AI” journey, and some are just getting started.  Larger companies have the resources to develop customized solutions, but the good news for smaller companies is that they have plenty of options for “buy” rather than “build”.  The catch?  There’s… a lot to choose from.  Commercial AI tools are popping up everywhere, and they’re increasingly powerful, purpose-built, and easy to use.  Vendors are already beating down your door to sell them to you.  It’s tempting to sign up for everything that sounds good in a rush to be “AI first” and show that you’re “doing AI”.

But why would you approach what may be the biggest transformation in your company’s history in such a piecemeal way?  I think a more deliberate, top-down approach will better prepare you for the future.  The challenge for small businesses is not in finding AI solutions, or even in understanding the technology.  The challenge is in developing a holistic corporate AI strategy and plan so that you can prioritize your company’s most important needs, optimize your budget and resources, avoid duplication and unnecessary thrash, and maximize the value that you realize from these solutions.

Your holistic plan would include processes for things like:

1. Discovery – determining which business processes, pain points, desired capabilities and business differentiators should be prioritized for AI
2. Developing an AI charter and policy – documenting the organization’s AI goals and expected timelines, approach, governance, and acceptable use
3. Evaluating and selecting solutions – focusing on solving high-priority problems and creating competitive advantages
4. Evaluating cost – from all angles: dollars, resources, change, and time
5. Reassessing the org chart and staffing projections
6. Educating users
7. Educating business leaders

…and (8) – last but definitely not least – focusing on your company’s data, which we’ll cover next.

DATA DATA DATA!

OK, this part is less exciting, but the most important thing about AI might not be the technology itself.  All value derived from AI starts with the underlying data!  The “garbage in garbage out” rule applies here. 

Every company is sitting on a mountain of data, collected over years, which, if leveraged to its fullest potential, could provide a competitive advantage and differentiation in their market.

At its core, what does AI do?  It takes mountains of raw data and turns it into refined, accurate deliverables in specified formats.  If you want to pave the way toward a bold future where AI is producing valuable deliverables specific to your business (hint: you do), then your business data has to be clean, standardized, and complete.

So while you’re evaluating which business processes and capabilities you want to prioritize for AI projects, at the same time you’ll need to be looking at the underlying data that enables those processes and capabilities.  Often this data will be spread across multiple systems.  For example:

• Customer service initiatives may require data from CRM, tech support, accounting, and contract management systems
• Data analysis initiatives may require data from purchasing, inventory, laboratory, and manufacturing systems
• Research initiatives may require data from emails, internal documents, policies, white papers, case studies, position papers

TIP for 2025: Understand “RAG” AI (Retrieval Augmented Generation) – this is where an SLM or LLM (small or large language model) is used to generate the core response but additional data is also brought in from external systems to augment the response.

To be clear, data hygiene has long been a major business concern.  The goal of maintaining consistent, accurate, clean data – and standardizing it across platforms and eliminating data silos – is nothing new.  But AI is bringing this concern to the forefront, and many companies are finding they need to undertake data cleanup efforts before, or alongside, their AI initiatives.  

The reward?  Commercial AI platforms are enabling processing and integration of large, diverse data sets in a way that small companies could never achieve before.  This is lowering the barrier of entry to “big data” style analysis that large companies have been leveraging for years.

SECURITY

As you can probably imagine, AI presents cybersecurity with a very sharp double-edged sword.  It’s a powerful tool for both the bad guys and the good guys.

• Bad guys: AI enhancements are already resulting in breaches that are more frequent, more efficient, easier to carry out, and on average more expensive for victims.  AI-facilitated ransomware is a major threat (and is currently a favorite tactic for political retaliation by nation-states).  AI has made phishing and other scams, like deep fakes, increasingly sophisticated and targeted.  And new types of attacks have emerged, like prompt injection attacks that can extract confidential information from generative AI systems.

• Good guys: AI is able to enhance almost every aspect of threat defense.  It can improve detection capabilities for intrusions, phishing, and malware; it can enable more accurate threat assessments, more refined alerting, and better/faster automated responses.

So, while it’s true that cybersecurity is much more automated than it used to be, so is cybercrime.  Although many companies are watching their spending right now, business leaders need to be aware that cybersecurity is on the front lines of the AI “battle”.  It is more complex and arguably more critical than ever.  Therefore, security is not an area where it’s advisable to replace employees with AI anytime soon.  Yes, AI will improve efficiencies of security teams, but skilled humans are still required to stay abreast of threats, configure the tools, understand the information and responses they generate, take appropriate actions, and communicate with management and clients.

Business leaders should also be aware that there’s a huge cybersecurity talent shortage right now.  So the advice here is, take care of your existing in-house security talent (continue to hire, retain, and upskill), and be aware that mitigation of cyber threats is always multi-faceted: it includes not just AI-powered detection and response tools but also proper access controls, fraud controls, and user training.

NOTE: Of particular concern right now is the public sector, because of its volume of sensitive data, attractiveness to foreign actors, and the fact that the public sector has been slow to adopt AI practices.

CONCLUSION

AI is here, and it is the future.  Have a plan.  Build your AI chops aggressively within your plan.  Use it to solve business problems – evaluate the suitability of available AI solutions for your key processes, pain points, desired capabilities, and competitive differentiators.  Build custom AI solutions if you have the resources to do that, but home-grown solutions will be increasingly unnecessary for small companies.  A certain degree of failure is OK in the early stages – you are building your organizational AI muscles.  Train your staff.  Train your business leaders.  Hire with an eye to AI skills – a good rule of thumb will be to screen for AI skills or AI literacy when hiring in almost every role.

Again, approach this with the assumption that eventually AI will take over all aspects of how you run your business – assume you will be “under water” in just a few years.  2024 may have been the last year that small companies could be tentatively sticking their toe in and splashing around.  By 2025 you really need to have learned how to swim.

And finally, this is the part where I let you know I can help. If the above seems big, scary, or complicated, I can help your business assess its AI needs, put these principles into practice, and chart an AI journey that sets you up for the long haul.