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A Primer to Artificial Intelligence

in Business


With all the recent talk about artificial intelligence, machine learning and robots taking over the world, the terminology can be a bit overwhelming. There is a lot of misinformation on these topics and unless you have a PhD in Computer Science, it can be difficult to separate fact from fiction.  You’re probably wondering what artificial intelligence (AI) is on a practical level and how it will impact you and possibly your career. So let’s set the record straight on what exactly AI is (and isn’t).

Simply stated, artificial intelligence is the ability for computers to perform tasks as well, if not better, than humans. AI can be applied to any scenario where machines can be “trained” to perform specific tasks, much the way a human would, by the bot training itself or by humans teaching it.

Artificial intelligence relies heavily on machine learning algorithms to create the cognitive capabilities needed to think like a human. Predictions have existed for years about what AI would look like – all with dubious degrees of accuracy. The visions of a world subservient to robots, as depicted in science fiction movies, are more reflections of Hollywood’s creativity than actual reality. Although machines don’t quite live up to the Hollywood depiction, there are many useful applications for artificial intelligence in today’s world.

This guide to artificial intelligence provides an overview for how AI works from a business perspective and how it can be beneficial to companies now and in the future. 

Artificial Intelligence Today

Here are a few key terms to understanding the world of AI:

  • Machine learning – The ability for computers to improve functionality based on a variety of algorithms including pattern and text recognition. Over time, as it has more reference data, the machine learns to become more efficient.
  • Natural-language processing – A process that deals with a computer’s ability to analyze language through speech recognition, semantics and syntax. Just like a human learns a language through listening and reading while understanding the context, computers can attain a similar capability.
  • Deep learning – A broader version of machine learning, deep learning is the ability for a computer to process various pieces of information the way a human would to make informed decisions and judgements. Deep learning uses neural networks to prioritize data by assigning a numerical value to each data point or using true/false logic analysis.
  • Neural networks - Neural networks refer to the vast clusters of data within a computer system that leverage their proximity to other related clusters of data to increase each cluster’s ability to learn from the other, much the way the human brain and nervous system do.
  • Support vector machines (SVM) - SVM technology allows machines to identify optimal solutions when faced with multiple options. Machines are typically fed a small set of data samples (which are the support vectors) to help it find an optimal solution.
  • Supervised vs unsupervised learning - Machine learning often contains three types of learning: supervised learning, semi-supervised and unsupervised learning. In supervised learning, the “answers” the machine is supposed to learn for understanding rules of classification, data extraction, and analysis are given as ground-truth during training. For unsupervised learning, the intended answers, or equivalently machine output, is not provided. Any rules or inferences the machine learns are determined strictly using machine learning algorithms, independent of having been provided the answers a priori. Semi-supervised learning falls between structured and unstructured learning.
Most of us engage with AI daily and often do not even realize it. Amazon Alexa, Pandora and Netflix, to name a few, all leverage AI technology to learn more about user profiles and preferences.  These AI-based systems then use this knowledge to deliver a more personalized experience based on learned patterns of behavior.  This technology enables music and video streaming services to make recommendations and allows automated personal assistants to anticipate requests. What’s the end result? Thanks to AI, homes are getting smarter and life is being simplified.

Likewise, businesses also have plenty to gain from the adoption of AI into their environments.

In its current state, AI’s ability to automate historically manual processes makes it a valuable business tool when combined with machine learning.  Here are a few examples where AI can play a role.

  • Natural language processing for document review – A business often has thousands of documents that typically require a human to crosscheck entries for completion or ensure that it meets various laws or compliance regulations. Instead of building pivot tables and performing lookups across thousands of spreadsheets, a machine can learn the information needed to complete the task and classify documents quickly. It can also determine the type of document the machine is looking at, so it can extract different types of data based on the rules it learns.
  • Extraction of data from documents – Businesses often use data from a multitude of documents to file reports for clients and internal purposes. However, the task of extracting that data can be tedious, labor intensive and time-consuming. AI makes reporting easier by allowing users to automatically obtain the data they’re looking for within a set of documents.
  • Detecting anomalies within data – Machines can look at vast amounts of data to identify likely anomalies automatically. An example is a bank’s ability to identify unusual banking activity, providing tighter security against consumer fraud.
  • Learning from voice, image and text data – Businesses can greatly benefit from AI’s ability to recognize image and data within various documents and learn what they are, so it can classify these items at a rapid pace. When the machine is given a certain taxonomy to learn, including how each document class is processed and treated, it will then handle subsequent documents exactly how it was trained with a high degree of accuracy. This allows the machine to process complex documents, which might normally require hours of training for humans, in “real-time”, i.e., a matter of seconds. 

Industries that Benefit Most from Artificial Intelligence

Artificial intelligence has completely altered the knowledge worker’s office efficiency. Rather than spending hours doing repetitive, often menial, work, where fatigue has been shown to have a strong negative impact on job performance, valued employees are now able to focus on more creative tasks—providing greater benefit to their employers and giving those employers a significant edge over their competitors.

Several industries have already experienced varying levels of success with AI and are likely to implement it on a larger scale in the future. For example, most of the “Big Four” tax and accounting firms already rely on AI to comb through, classify, arrange, and analyze millions of pages of client documents with higher accuracy rates and much faster processing speed (often on the order of 100x-1000x) than when the same work was done manually.

But tax and accounting isn’t the only industry to benefit from implementing AI. In fact, nearly every business process will see a significant improvement in performance through AI. For example, the finance industry uses AI systems to analyze market behavior, build trading algorithms, check for money laundering, and manage underwriting and investment processes. Artificial intelligence also benefits document-intensive industries such as mortgage banking, accounts payable, and insurance, where it improves the speed at which documents can be processed and business processes solved. 

Misconceptions of AI

After reading about all that AI can do, you might still have some concerns.

There are several myths around AI’s perceived threats and capabilities. Here is a list of some of the biggest misconceptions and the truths surrounding them.

AI can do everything

Although there is so much that AI can do, it will never be able to solve problems in the same way that humans can. While bots can mimic human behavior, and perform tasks with greater efficiency and accuracy, they cannot perform any task without human direction. AI is best-suited to optimize and/or automate a business process when it’s solving a problem of efficiency, speed or accuracy and there are specific guidelines for it to follow.

One of the business use cases of AI is to learn highly redundant, repeatable processes. In learning these processes, an AI-based solution can often repeat these processes thousands of times per minute, with absolute precision.

AI requires that experts train the system so that it has the knowledge to perform these domain-specific tasks. In addition to training, the system needs a large dataset and ample information to enable the machine learning processes. Depending on the complexity of the data, this can sometimes be thousands of documents and/or data points.

Bots will take my job

Although it’s true that AI might eliminate the need for some jobs, the overall notion that we’re going to end up on the street because every task imaginable will be automated is entirely false.

In industries that have implemented AI to automate workflow processes, employees are finding themselves tasked with more meaningful work and are more valued and feeling more fulfilled at their jobs than before.

Like other technological advances in history, there are some industries that will be affected more than others. Companies will adapt, as they have for years, and will find innovative ways to become pioneers in their fields using the latest cutting-edge technology for increased productivity.

 Through the implementation of AI technology, employees can feel greater satisfaction at work and employers can easily scale up their processes to meet the increasing needs of a growing market.

AI technology isn’t safe

There are a host of concerns regarding the safety of artificial intelligence – some more legitimate than others.

Gone are the days when people feared that humans will be destroyed by robots, but in the 21st century we have other, very real safety concerns stemming from the advancement of technology.  Data security has become one of the greatest threats to each of us. Nearly every day, it seems that a new business is getting hacked, putting valuable customer data at risk. Yet, most businesses lack the necessary tools needed to truly protect themselves against a data breach.

Because of potential vulnerability, businesses are reluctant to trust AI with documents containing personal information, whether it’s a loan packet, tax return, corporate audit, patient medical record or some other area of their core business processes that can be improved using AI. The reality is that even if the data is shared with a bot, when hosted properly on a secure network, the data is actually more secure.  Using reliable data security methods, such as encryption and data redaction, personal information can be secured and protected, even if the document workflow includes AI and machine learning modules.

Companies looking to invest in AI technology should certainly ask questions regarding data security. But many of the concerns related to how a machine will use that data are often exaggerated or misinformed.

Only programmers can use AI technology

Having a technology expert on-hand is certainly advisable when it comes to implementing an AI solution. However, you don’t need to be an expert software developer to use AI as it becomes more user-friendly to the public.

Though AI systems are complex and require high level expertise to develop, through a user friendly graphic interface, systems are designed to be easy to manipulate.  Even when AI tools require users to have some technical abilities to correctly implement, most software also relies on implementation specialists to optimize the system requirements and ensure that the software will work in the business’s environment.

To recognize the true value that an AI solution can offer, the technology must be paired with industry leaders and thinkers who bring value to the addition of technology to the workflow process.

Only then can the technology truly work to its potential. 


the history of artificial intelligence


The Future of AI

According to Tractica, the AI market is expected to reach $36 billion by 2025 – a 57x increase from where it stood in 2016 at $644 million – making it the fastest growing technology in the IT sector. By that time, nearly every vertical market will employ AI technologies in some compacity.

For businesses that rely on knowledge workers, there are a few interesting trends to watch in the next few years.

The Machine as the Decision Maker

At full capacity, artificial intelligence won’t only process information faster, but will also be instrumental in making the decisions.

As machine learning gets more advanced, an AI system will have the ability to understand raw data and weigh it against a set of rules humans might use to make decisions. The advantage of using a bot is that rather than extracting data and forcing a group of experts to spend time mulling over the costs and benefits of certain outcomes, a machine could weigh those factors in real-time and make a recommendation.

For businesses that are looking to speed up the decision-making process, AI has the potential to become a true game-changer. For example, using an AI application a college admissions counselor trying to decide on whether or not to accept a student and how much credit to give for transfer credits can have decisions for thousands of students made in just minutes.

As AI becomes more relevant to business processes, human intervention will still be required to verify and “tweak” AI determinations.  As the machines get “smarter” the amount of human involvement will decrease and the machine will become more autonomous and efficient.   

Once that happens, humans will only be required to give the final say or provide context to the AI system’s decision.

Companies that have consultative or advisory roles and invest in AI technology to improve the decision-making process will have a clear, competitive advantage over those who don’t. Whether it’s helping a company make more strategic decisions or using AI to further empower human workers, AI processes will help business advisors become better client assets.

AI in Blockchain

Blockchain technology has disrupted the transactional marketplace by becoming the new foundation for digital currency. As a decentralized digital ledger, blockchain is the only public and verifiable system that allows for transparency without opening itself up to being corrupted. 

By having a reliable framework, most of the due diligence that normally would be tedious or restrictive is eliminated from highly regulated areas such as mortgage lending or insurance underwritting. Instead of relying on a third party to ensure the information in each packet is accurate and compliant, the blockchain creates an immediate trust.

AI can help make blockchain a more mainstream and reliable technology for businesses by automatically analyzing enormous quantities of documents, allowing businesses to spend more time on growing their business. AI and blockchain used in tandem can commoditize assets and enable digital marketplaces in diverse areas including student admissions, receivables-based factoring, and mortgage lending.  

For instance, banks looking to sell thousands of loans may need to wait days for potential bidders to evaluate the relevant loan documents and perform their due diligence. By combining AI and blockchain technology, a machine could go through every loan packet across the servers they’re hosted on and perform most of the due diligence work within minutes.

In the current state of mortgage banking, over 70% of all costs are spent on manual data entry and re-assembling the data to facilitate the review process.  Often, this task is outsourced, making it prone to accuracy issues, security concerns and processing delays.

Using AI to perform due diligence through blockchain not only eliminates the time needed for document analysis, but also reduces processing costs. Instead of spending resources on compliance, banks can focus on evaluating loan risk and quality to grow their business and increase their profitability.

As more institutions begin to trust blockchain as a framework for financial transactions, its ability to combine with artificial intelligence creates a unique opportunity for businesses in regulatory industries. While blockchain is in an early adopter stage, it has room for significant growth. Statista projects blockchain to be a $2.3 billion industry by 2021, with the first leap in adoption expected to hit as early as 2019.

By merging the power that AI technology provides, blockchain technology will not only impact businesses for the better, but provide the greater economy with a standard operating model for transactional behavior. 


Practical artificial intelligence already has the capability to create game-changing results for businesses by empowering today’s knowledge worker. AI will never overtake humans in society, but its ability to perform every day human tasks quickly and accurately within the workplace makes it an essential technology for businesses to tap into to improve employee performance and efficiency.

Through its various techniques, there are no limits to the potential for AI and machine learning to provide meaningful business value in almost every industry imaginable.

About SoftWorks AI

SoftWorks AI is dedicated to helping businesses enhance operational efficiency by providing reliable, innovative, automation solutions. We strive to leverage our deep expertise in OCR, advanced data capture, and AI technologies to convert raw information into actionable insight, equipping knowledge workers with the means to drive business value faster and more intelligently.
We are artificial intelligence and machine learning experts with proven solutions that automate and optimize complex processes. SoftWorks AI solutions possess deep vertical knowledge coupled with advanced technologies to drive substantial ROI. We also have a diverse client base, including many Fortune 500 companies.

Do you want to know how AI and machine learning can provide value to your business? Contact us today for a free 30-minute consultation on the business impact of artificial intelligence. 

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