Machines that can think. Machines that can independently solve problems. Two decades ago, concepts like these were only possible in the movies, but fast-forward 20 years later, and it’s old news. 

Now, businesses aren’t considering the feasibility of the technology, but rather its implementation. Artificial intelligence (AI) has always been a polarizing subject and in the tech industry, there are staunch, opposing sides. 

Today, enterprise companies appear to be leaning against incorporating AI solutions into their mobile apps for several valid reasons. But before we discuss those points, what exactly is this “AI” and how does it work?

What is Artificial Intelligence?

Artificial intelligence is the engineering of human thought patterns into a machine, especially computer systems. It is a mimicry of man’s behavior reflected on a piece of equipment, a simulation of human intelligence. Applications of AI in specifics include; speech recognition, expert systems, natural language processing, and machine vision.

AI systems function by collecting massive amounts of specifically labeled training data, analyzing them for patterns and correlations before making calculated predictions. Take a chatbot, for example, a machine fed with limitless samples of text chats to produce lifelike replies with real people. AI programming is focused only on learning, self-correction, and reasoning — three cognitive skills. 

There are two categories of Artificial Intelligence; weak and strong. The weak AI, usually referred to as ‘narrow AI’ is designed and programmed to perform singular tasks. Most virtual personal assistants, including Apple’s Siri, utilize weak AI.

Also known as artificial general intelligence (AGI), Strong AI solutions were programmed to study and replicate human cognitive abilities. It makes use of ‘fuzzy logic’ to find solutions to complex or unfamiliar tasks. 

Now that we understand what AI is and how it works, let’s dive into why enterprise companies are dubious about accepting them.

Read more: Python AI: Why Python is Better for Machine Learning and AI

7 reasons why enterprise hesitates to integrate AI in mobile apps

1. Worries about Cost

Profit is the number one goal of a successful company. So, it’s no surprise that expenses are among the reservations that enterprises have over Artificial Intelligence. Although AI opens a whole world of possibilities on effectiveness, the bottom line is the machinery is expensive. 

Being familiar with the cost — both monetary and labor — required in the integration of AI into mobile applications. These companies are also aware that AI will need a lot of costly updates to blend with rapidly changing trends and business requirements. 

Also, if there is a major system breakdown, AI-enabled machines will need lengthy processes to be reset. This in turn depletes monitoring operators, leading to additional costs. 

2. AI is Untested Waters

There is a lot of buzz, generally positive, around the potential benefits of AI in essentially every sector. But the undeniable fact is that Artificial Intelligence is still a relatively new industry and there are still a lot of unknowns. This uncertainty makes for an increase in risk to capital, as trust in it hasn’t been fully established yet.

This is why most digital brands prefer to go the conventional, known route. They prefer to utilize ready-made analytics and the mode of user interactions to gain and satiate customers with the help of a mobile app development company.

3. There’s No Human Element

Many businesses have built their brand on human-to-human connection and AI — despite numerous efforts — still lacks the intelligence and emotion factor. AI-induced machines and robots aren’t yet capable of consistently making steadfast decisions. 

Artificial intelligence is programmed to be entirely mechanical. Due to this glaring flow, enterprise companies think AI has too many limitations to consider incorporation. They still doubt its capability to function optimally in crucial circumstances.

4. Limited Knowledge of AI

AI has a vast framework that becomes subject to modification when several technologies interlink to find a problem’s solution. Machine intelligence, unlike humans, never gets complacent or static, it is an ever-evolving entity that is dynamic and innovative. This is hard for some businesses to come to terms with when they deploy custom software development services, so they can’t accept an exclusive AI model.

Change is hard, but the capabilities of AI offer drastic changes that people aren’t yet prepared to make. So, although statistically, 88% of business owners use resolutions dependent on AI applications, they are still doubtful.

5. Loss of Control

Several individual parts of the human body serve different but equally vital functions. However, fundamentally, the brain is the mastermind behind every operation. At first, execution tasks were automated, then real-time feedback and internal marketing systems. 

Enterprises are wary of giving the autonomy of decision away, especially to a soulless machine. Incorporating AI into the decision-making process takes the sense of power away from corporate heads, and they aren’t prepared to rescind it. 

6. Operation Demands High Resources 

There are several benefits to the use of AI, but its implementation is a very tasking process. It requires a considerable quantity  of natural language processing, predictive analytics automation, and human resources to develop intelligence. 

Also, apps powered by Artificial Intelligence must have high adaptation capabilities and be programmed to process data inputs intuitively. So, if you experience financial constraints, there’s a huge chance you won’t efficiently leverage AI.

7. AI is Purely Mechanical and Knowledge-based

Humans have a fluid method of thought; we are naturally logical thinkers and also learn via our experience. This means that we develop a cognitive flow and understanding of the world that is steeped in reality. 

However, AI machines learn via information fed to them, with no experience attached to it. This means that its responses are bound to become redundant in time, due to inflexibility.

Checkout Artificial Intelligence vs. Machine Learning vs. Deep Learning

Why Virtual Data Rooms are not Implementing AI

A virtual data room software is a more secure alternative to cloud services, where your most sensitive information is supposed to be safe. The jury is still out on the efficiency of AI and seeing as VDR is also relatively new, there are still doubts.

Virtual data room providers are wary of incorporating a semi-alive into software that handles a lot of vital information. Data room providers recognize the upside of implementing AI but concerns remain. Until it gains more notches on the belt in the tech world, they’d rather stay where the ground is solid.


Since its introduction, AI has caused heated debates, splitting opinions on its impact both financially and on society. Due to its limited use in major processes, AI still struggles to convince Enterprise companies of its dependability long term for Android app development services. However, the potential benefits of AI largely outweigh the risks, so it’s only a matter of time before it comes to the fore.