Today’s businesses collect and process more data than ever before, and transact with customers through more channels. Traditional software can only partly address these needs. Business software is increasingly requiring systems that can go beyond simple data storage and/or rule-based control.
Organizations need business software that can analyze data, automate repetitive tasks, identify business processes and data flow, support user decisions, and adapt to changes in business requirements.
Intelligent software solutions are playing an increasing role in the business software ecosystem.
The combination of different, yet related, technologies, like artificial intelligence, automation, analytics, and integration, is making business software more capable and useful.
Sometimes a misconception sets in that just adding AI to an application increases its value. However, the real value comes from using AI or other related technologies to solve a business problem more efficiently, accurately, or quickly.
This guide explains what intelligent business software solutions are, how they operate, their key technologies, benefits to a business, major applications, how they are implemented, and what to consider before investing in them.
What Are Intelligent Software Solutions?
Intelligent software solutions are digital systems that use data, automation, analytics, and artificial intelligence to make decisions, or provide support for decisions, with more context than traditional software. Traditional software, in most cases, operates based on predefined rules. For example, a basic payroll system may calculate pay and issue checks based on the rules defined by an organization. An intelligent payroll system may identify rule violations, and in addition to suggesting the calculations, notify an employee or the system administrator.
There is a broad spectrum of human intelligence. Likewise, intelligent software can range from very simple rules-based automation to advanced technologies like machine learning, natural language processing, computer vision, predictive analytics, and generative AI.
The goal is not to fully automate the workforce. Leading intelligent software automates tasks, frees employees up to do more interesting, higher-value work, and provides a guide to facilitate the work.
How Intelligent Software Differs From Traditional Software
Traditional software is usually designed around fixed instructions.
A user performs an action, the software follows programmed rules, and a predictable result is produced.
Intelligent software can introduce another layer.
It may analyze historical information, interpret unstructured content, identify relationships between data points, recommend an action, or adjust a workflow based on available information.
Consider customer support.
A traditional ticketing platform stores a customer’s message and allows an employee to assign it to a department.
An intelligent platform may analyze the message, recognize its subject, determine urgency, identify the customer’s account, suggest a response, and automatically route the request to the most appropriate team.
Humans remain responsible for decisions where judgment or oversight is necessary, but the system reduces manual work around those decisions.
Core Technologies Behind Intelligent Software
Modern intelligent software solutions can use several technologies depending on the problem they are designed to solve.
Artificial Intelligence
Artificial intelligence is a broad category of technology that allows software to perform tasks associated with capabilities such as reasoning, language processing, pattern recognition, and decision support.
AI may be used for recommendations, classification, content analysis, virtual assistants, fraud detection, forecasting, and many other applications.
Machine Learning
Machine learning allows systems to identify patterns from data instead of depending entirely on manually created rules.
For example, a company may use machine learning to predict which customers are more likely to cancel a subscription based on previous behavior.
The quality of the results depends heavily on factors such as available data, model design, testing, and the problem being addressed.
Natural language processing, commonly called NLP, helps software work with human language.
Natural Language Processing(NLP)
It can be used for:
- Chatbots
- Document classification
- Search systems
- Email analysis
- Sentiment analysis
- Information extraction
- Voice assistants
- Customer support tools
Modern language models have significantly expanded the types of text-based tasks software can assist with.
Intelligent Automation
Intelligent Automation helps to handle repetitive processes that do not necessarily require human involvement.
Using AI, Automation and business workflow technologies, more complex processes can be fully or partially automated.
For example, a system can get a customer document, automatically read the document, check if the data is consistent with the company’s data, and automatically update an application, and only if something is inconsistent send the document to an employee for review.
Data Analytics
Data is useless if it can not be transformed into understandable information.
Through analytics, businesses can look at trends, understand customer behavior, examine employee performance, and help understand operations.
Some analytics software can even help predict future outcomes.
Cloud Computing
Cloud infrastructure can provide a platform to scale intelligent applications.
Instead of managing their own computing resources, companies can use cloud resources for computing, storage, databases, integrations, and AI.
For each company, the ideal infrastructure is based on their requirements for security, cost, performance, regulatory, and operations.
Major Benefits of Intelligent Software Solutions
1. Increased Operational Efficiency
Time is wasted on repetitive administrative tasks. Employees can spend hours on tasks like transferring data between different systems, email sorting and reporting, or data updating and searching.
Employees can free up time to perform tasks requiring critical thinking, communicating and interacting with others, and creativity.
2. Better Decision Support
Time constraints can prevent the analysis of all the data a company has.
Patterns in large data sets can be identified using intelligent applications, and these applications can help make recommendations for business decisions.
3. Improved Customer Experience
Customers expect companies to provide highly convenient, personalized, responsive, and interactive experiences.
Intelligent systems can help provide recommendations, communication, support, and access to information, thereby improving customer experience.
4. Reduced Manual Errors
Manual data entry increases the probability of errors. Automating repetitive tasks, like data entry, can help reduce the occurrence of errors.
Integration between different systems helps because data does not need to be manually entered in different platforms.
5. Scalability
As a business expands, so do the complexities of managing the business. This is especially true when a manual process is required for every aspect of the business.
Intelligent automation allows the business to increase its processing capacity and reduce administrative burdens on employees.
6. Better Use of Business Data
A lot of businesses collect data but do not use it effectively.
Intelligent apps can integrate with an organization’s data, analyze it, and present it in a more consumable format through alerts, recommendations, dashboards, or natural language queries.
Common Business Applications
There are a variety of ways intelligent applications can be used to improve common business activities.
Customer Service
Improving customer service through the use of intelligent applications helps consolidate customers’ requests, suggest responses, search knowledge bases, and summarize previous service interactions.
This allows employees to spend less time on mundane tasks and more time interacting with customers.
Sales and CRM
Sales personnel can use intelligent CRM applications to analyze their sales pipeline, and summarize and suggest next steps in customer interaction.
Predictive applications can help prioritize sales leads based on potential opportunity.
Finance and Accounting
Intelligent applications can help automate routine tasks in finance and accounting, such as invoice and expense document data entry and categorization, document and data extraction, and report generation.
Human Resources
Intelligent systems enable HR teams to automate tasks related to candidate management and employees, document processing, workforce analytics, and administrative tasks.
For example, an internal assistant can help employees find information about HR policies.
Manufacturing
Manufacturing companies can use sensors, analytics and machine learning to gain real time equipment and process insights. Predictive maintenance systems can be used to proactively identify equipment failures based on an analysis of equipment related information.
Healthcare
Intelligent technology has various applications in the healthcare sector ranging from administrative automation, clinical documentation to analytics and patient communication.
Because of the sensitive nature of the data, privacy and security of the information as well as appropriate controls need to be given due consideration.
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Intelligent software has many applications in the retail sector for customer recommendation systems, personalization, demand and inventory planning and management.
These can also assist with understanding customer needs and other requirements related to inventory.
Custom Intelligent Software vs. Ready-Made Platforms
Depending on a business’s requirements and resources, they have two main options: purchase and use a ready-made product, or have a solution developed to their requirements.
Ready-made products may be a good option when a product aligned with business requirements is widely available. They may also be less costly and more time efficient.
Custom intelligent software may be the more prudent option when a company processes are highly customized and unique to the business; especially if that business has valuable, hard to replicate data.
A company should look at various factors when making the decision; cost of implementation, licensing, maintenance, integration, security, scalability, business value and the skills of their employees.
How to Implement Intelligent Software Successfully
Identify the problem to implement technology, not the other way round.
Identify the Problem
Solutions should first be assessed by evaluating processes or tasks that are time-consuming, repetitive, data-intensive, and inadequately supported by existing tools.
Identifying the problem helps evaluate if intelligent software is the solution.
Define Clear Goals
Goals should be measurable.
If intelligence is added to business process management (BPM) suites, solutions could help business users evaluate the value of a system by determining if the system reduced the time needed to process documents, improved the speed of customer response, or reduced the time and data entry effort required to make reports available.
Evaluate Existing Data
Many AI applications incorporate and/or use data.
IT solution providers should take into account the legal, ethical, and moral implications and consequences of using the data.
Poor data will give poor results, and especially sophisticated technologies, will not change this.
Choose the Appropriate Technology
Not every problem requires the deployment of AI.
A basic integration of systems or an automation of workflows may better address the problem.
The most simple solution to a problem should be implemented.
Test the Technology
A solution should be adequately and sufficiently tested to reveal workflow and technical problems and to collect and validate user feedback.
Measure Results
Implement the change and then assess your results.
Consider measures such as time saved, reduction in processing errors, acceptance by the end-users, average time to serve the client, cost associated with the service delivered, and others.
If the technology doesn’t yield positive impacts, adjust the process or solution.
Security, Privacy and Responsible AI
As software becomes smarter, managing it becomes more important.
It is important for an organization to be informed on the types of information their systems process, the protection of the information, how the decisions are made, and where human oversight is required.
Among the factors to consider are:
- Data privacy
- Access controls
- Cybersecurity
- Output accuracy
- Transparency
- Reliability
- Human review
- Bias management
- Monitoring
- Regulatory requirements
While using intelligent technology, businesses need to consider testing and the impacts of AI.
Adequate checks, controls, and human oversight should be considered for higher impact decisions.
Responsible implementation helps organizations utilize intelligent technology and mitigate risks.
How to Choose an Intelligent Software Provider
When evaluating an AI software provider, it is not enough to review a list of features.
Start by checking whether the provider understands your business problem.
Adequate providers should be able to provide reasoning for their suggested technology.
Consider:
- Relevant industry experience
- Software-development capabilities
- AI and machine-learning expertise
- Security practices
- Integration experience
- Data-management approach
- Testing procedures
- Scalability
- Maintenance and support
- Communication and documentation
Prior to initiating a major project, it is prudent to review and clarify the above.
What Will Business Software Look Like in the Future?
Traditionally, business software helped organizations store information. Now, the focus is shifting to helping organizations work with the information stored in the systems.
AI assistants can help simplify the use of enterprise applications with natural language interfaces.
Automation can help merge processes that currently require employees to move between applications to help perform a specific task.
Analytics can help focus on relevant changes instead of requiring employees to search through dashboards to find information.
The value of a software solution will not be determined by the amount of AI it contains.
Organizations will continue to value software solutions that are useful, reliable, secure, easy to understand and cost-effective.
Final Thoughts
Intelligent business software can help organizations easily automate repetitive tasks, make better use of their data and improve their services, products and offerings.
However, improving the customer experience and creating software solutions that help employees make better use of their time and improve workflows should not only be the focus of innovative technology solutions.
These challenges can best be solved by intelligent technology solutions that address a legitimate business need.
The focus should be on the problems that a given solution will help address rather than automating every mundane task.
Successfully implementing innovative, reliable and intelligent technology solutions can help shape better how employees accomplish tasks and make decisions to improve the growth of an organization.
Frequently Asked Questions
What do you mean by intelligent software solutions?
Intelligent software solutions use various technologies like Artificial Intelligence (AI) and machine learning to automate, analyze and support the business to make better decisions.
How can intelligent software help businesses?
Intelligent software can automate mundane, repetitive tasks; provide easier access to data; support business decisions; reduce manual processes; enhance customer service and help staff to manage increasing workloads.
Does intelligent software always involve AI?
No, not always. While some intelligent software solutions integrate AI extensively, others may use business rules, workflow automation, analytics and integrations and some machine learning.
What kinds of businesses can use intelligent software?
All kinds of businesses ranging from healthcare, financial services, retail, manufacturing, logistics, education, professional services, technology and others can use intelligent applications to address business problems.
Is it expensive to develop intelligent software?
The cost is determined by the level of complexity, the features required, integrations, data and AI models. Additionally, cost may be determined by the infrastructure required to host it and the level of security the company wants to build it.
How should a business start with intelligent software?
A business should start with a focused problem instead of an extensive AI project. The project should have measurable objectives and review the data available before investing in technology.
