The thing about large institutions is that they rarely struggle from a lack of ambition. More often, they are held back by decades of accumulated processes, disconnected systems, and growing administrative demands.
Every institution, be it the government, banks, correctional facilities, or educational institutions, is vulnerable to this. As a result, software and artificial intelligence have become central to conversations about improving efficiency.
The question is, do they really help? In this article, we’ll find out if large institutions should actually invest in software and AI or if it doesn’t really make a difference. We’ll explore why some institutions seem to stay inefficient and why the solutions aren’t as straightforward as they should be. Let’s jump right in.
Blind AI Usage Doesn’t Guarantee Performance Boosts
It’s always good to start with the elephant in the room, and currently, that’s AI. For the last few years, it has dominated discussions about efficiency. Yet, for many organizations, the actual impact isn’t as transformative as it’s hyped up to be.
According to data scientist Sarthak Gupta, when AI is adopted, it creates an automation phase that creates more upfront work. This involves building pipelines, iterating tools, and retraining workflows. Business Insider also highlighted research, which showed that 90% of companies actively using AI reported no real productivity boost.
At the same time, once key automation objectives have been achieved, it can unlock a new layer of efficiency. However, very few companies seem to know how to deploy AI in the right way.
It’s why PwC also observes that 74% of AI’s economic value is captured by just 20% of companies. Their research found that effective companies were 2.8 times more likely to have increased the number of decisions made without human intervention. It’s worth remembering that the reason these companies are effective in the first place could be due to factors unrelated to AI itself. It’s just that they tend to use automation at a higher level than others.
So, AI can help, but it really requires a degree of agility that large institutions might struggle to muster. They can deploy and integrate AI, but the likelihood of fast efficiency gains from simply using it is not always guaranteed. The reason? A lack of agility.
The Agility Challenge That Plagues Large Institutions
The complexity of large institutions extends far beyond what most commercial software and AI tools were designed to handle. They tend to coordinate services across multiple departments, manage enormous transaction volumes, and deal with complex legal compliance factors. Given this kind of environment, it’s easy to see how tough it is for either software or AI to integrate cleanly with the system.
Take banking, for example. According to Glenn Fleishman, a freelance journalist familiar with aging digital infrastructure, more than 40% of American banking systems run on COBOL. That’s a programming language that’s over 67 years old now. Fleishman points out that the language is deeply embedded not just in financial systems, and replacing it would cost millions or even billions.
Many institutions continue relying on these inefficient systems because introducing software or AI introduces considerable financial costs and operational risks. That said, specialized software still has a role to play in compartmentalized areas. Look at correctional facilities and juvenile detention centers. They represent another large institution with several moving parts.
Yet, specialized software can simplify and automate a smaller subsect of tasks and operations. So, a detention center for those under 18 might use juvenile justice software that can help track behavioral trends, therapy participation, and more.
As JailCore explains, such systems also include monitoring devices that officers can use to keep track of things. What’s unique about this is that it doesn’t set out to automate the entire correctional system. Instead, it targets key areas with focused solutions. That’s how efficiency is created in institutions.
AI For Efficiency Is Still in the Sights of Many Governments
As one survey by Gartner shows, 55% of Government CIOs outside America said they will focus on boosting employee productivity in 2026. This priority was supported above those that sought to launch new digital products/services (38%) and those that improved overall citizen experience (37%).
In other words, governments are clearly open to AI as a practical way to improve productivity. However, whether they understand the difficulty in creating actual efficiency boosts remains to be seen. The risk of AI creating more upfront work, as mentioned earlier, continues to exist.
That said, there are some areas that AI can be perfect for in the context of government work. Public departments generally manage large volumes of paperwork and repetitive administrative tasks. This makes them well-suited for AI-assisted workflows. Of course, public servants will need to verify and ensure AI hasn’t made any errors, but it should free up some time.
Likewise, the drafting of emails and requests, something that government workers spend a lot of time on, can also be done with AI. Likewise, summarization of reports along with scanning and organization of forms are great ways that AI can help with overall government efficiency.
It goes without saying that the same concerns of liability and security risks have to be addressed. As author Isaac Asimov famously wrote, “Humans, not robots, are responsible agents.” So, until we find a way to bridge that gap, the efficiency gained from AI and software will always have one layer left unfulfilled.
Frequently Asked Questions
What are legacy systems, and why are they difficult to replace?
Legacy systems are older software or technologies that organizations still depend on for their daily operations. Replacing them can be expensive and risky because they often support critical functions, store decades of data, and connect with many other systems that also need to keep working.
Why does AI integration fail to deliver expected results in some institutions?
AI often falls short when organizations expect immediate improvements without preparing their existing processes. Poor data quality, outdated software, disconnected systems, and limited employee training can all reduce its effectiveness. Many institutions need to strengthen their operational foundation before AI can deliver lasting value.
What features should institutions look for in management software?
The best management software should be easy to use, secure, and able to grow with the organization. Features like centralized records, workflow automation, reporting dashboards, role-based access, integration with existing systems, and reliable customer support can make daily operations much more efficient.
Key Numbers & Facts at a Glance
| Percentage of companies that capture 74% of AI’s economic value | 20% |
| Key action taken by effective companies | They are 2.8 times more likely to use automation |
| Percentage of American banks still using COBOL | More than 40% |
| Percentage of companies reporting no productivity boost from AI | 90% |
| Percentage of government CIOs prioritizing employee productivity | 55% |
Software and AI can absolutely improve efficiency within large institutions, but it’s not a straightforward path. Some institutions, like banks, have deeply embedded legacy systems that slow modernization. Meanwhile, others, like correctional facilities, can compartmentalize and are able to reduce administrative burdens with software.
So, for any institution wanting long-term digital transformation, the question is whether the environment can be created for AI or software to operate effectively. If the environment isn’t conducive, you’re likely to see similar results to the 90% of companies that report no real productivity boost.
