🎉Celebrating 25 Years of Tech Excellence and Trust - Learn More

Software Development
Published: Jul 4, 2024

Why is Enterprise AI a Must-Have for Modern Businesses?

Verified
Verified Expert in Project management
Dhaval Dave, a Operations Spearhead, and a technology enthusiast at Radixweb.
Enterprise AI for Business Growth

A Quick Heads-Up: Written for organization executives, leaders, or anyone with an interest in the application of artificial intelligence in business, our article decodes the sometimes-confusing topic of enterprise AI using concrete information and practical examples. Enough of lagging behind your friends and colleagues when discussing enterprise AI!

Remember how AI used to feel like a concept straight out of science fiction novels and blockbuster movies?

Today, the picture is different.

From chatbots that assist customer queries to predictive analytics that fine-tune business strategies, artificial intelligence services and solutions have come a long way.

In the meantime, enterprise AI is taking center stage across various industry verticals. It has become an integral tool of the modern (and future) enterprise ecosystem that empowers organizations to thrive in this data-driven world.

If you look at the recent AI statistics, the global AI market size is going to reach $1811.8 billion by 2030. At present, 56% of enterprises are utilizing AI and 92% believe that AI will have at least some impact on their industry.

As a Pioneer of AI, We Help You Leverage It's True Power and Grow Exponentially

Start Your AI Journey

That brings a few important questions to the table – what does enterprise AI mean? What are its distinct advantages? How can you implement it? What challenges should you be ready for? And couples more.

Shall we find the answers?

On This Page
  1. What is Enterprise AI?
  2. How Does Enterprise AI Work?
  3. Top Use Cases of Enterprise AI by Industry
  4. Practical Applications of Enterprise AI
  5. Benefits of Enterprise AI Solutions
  6. Challenges of Adopting Enterprise AI
  7. How to Get Started with Enterprise AI
  8. Most Popular Enterprise AI Platforms
  9. Get Enterprise AI-Ready with Radixweb

What is Enterprise AI?

In layman’s terms, enterprise AI refers to a wide category of AI-based technologies, tools, and systems that get integrated into the core operations and processes of an organization.

Considering the mounting volume of datasets in an organization, we’re seeing the emergence of a new, enterprise-level AI technology that empowers teams to evaluate mounting datasets at scale.

Enterprise-grade AI is also the bedrock of digital transformation, as acknowledged by 95% of executives.

As an omni-use technology, AI can provide data-backed insights and improve the efficiency of almost any enterprise operation, such as sales and marketing, cybersecurity, customer service, etc.

Here’s how global enterprises are expanding the use of AI-based solutions across multiple fields, as IBM reported:

 Enterprise AI in Multiple Fileds

How Does Enterprise AI Work?

Technically, enterprise AI is based on a blend of technologies and processes to deliver the desired intelligent solution.

Here are the five critical components that define the workflow of an enterprise AI software system:

Enterprise AI Workflow

  • Data Collection and Integration

It all starts with the learning phase where the system gathers both structured and unstructured data from various sources.

  • Data Preprocessing

This part, aka reasoning, involves cleaning and modifying data. Enterprise AI platforms select the most suitable algorithm to use in that particular dataset.

  • Machine Learning Models

ML is the cornerstone of enterprise AI applications. These models can learn from experience, improve on their own, recognize patterns, and make classifications and predictions.

  • Natural Language Processing

NLP technologies analyze and structure human language. This allows AI systems to interpret texts, extract information, and generate human-like responses.

  • Deep Learning

It's a subset of machine learning that has the capability to deal with complex data like speeches, images, and videos. In autonomous robots, this technology works as a building block.

  • Feature Engineering

In feature engineering, you can organize and extract raw data to create new features or improve the existing ones.

Build an Advanced Enterprise Software System to Solve Your Specific Pain Points and Deliver Quantifiable Results

Take the Lead

Top Use Cases of Enterprise AI by Industry

From startups to SMEs and large-scale enterprises, every organization has come to realize that AI is likely to play a crucial role in enterprise software development and their overall business operations.

As a result, we’re seeing a growing adaptation of enterprise AI across multiple industries and departments, as shown in the image below:

Use Cases of Enterprise AI by Industry

Let's discuss the popular enterprise AI use cases in detail:

IT and Software Development

The IT consulting services sector was the first to embrace the power of enterprise AI programs in its day-to-day tasks.

Adoption Rate/YearDeployment AreasCommon Challenges
75%Automation of IT operations and software asset management, cybersecurity, downtime preventionData privacy and security, outdated infrastructure

Financial Services

As an early adopter of any new technology and trend, the finance industry has been quick in implementing enterprise AI systems for a broad range of use cases.

Adoption Rate/YearDeployment AreasCommon Challenges
61%Digital security, fraud detection, risk assessment, personalization of servicesData access, biased models, regulatory compliance

Healthcare

Automation capabilities of AI in healthcare transformed the way this sector works and manages its everyday operations.

Adoption Rate/YearDeployment AreasCommon Challenges
54%Patient data analysis, clinical workflow optimization, disease diagnosis, patient monitoringSkill shortage, restricted budget, regulation and governance

Manufacturing and Supply Chain

Cost and time efficiency are the greatest benefits of AI integration in manufacturing firms, which has resulted in a steady adoption rate of enterprise AI in this industry.

Adoption Rate/YearDeployment AreasCommon Challenges
42%Quality assurance, product design, prescriptive maintenance, inventory and route managementAccess to clean data, lack of talent, edge deployments

Retail

As retail stores are increasingly moving from their brick-and-mortar stores to online platforms, the need for AI solutions is at an all-time high.

Adoption Rate/YearDeployment AreasCommon Challenges
57%Demand/supply prediction, customer behavior analysis, inventory managementSecurity threats, integration with existing systems

Practical Applications of Enterprise AI

Here are a few important examples of real-life enterprise AI applications (you might very well be familiar with all of them):

1. Autonomous Vehicles

Automobile manufacturers are now building self-driving vehicles with the help of decision/rule engines, edge computing resources, and data-collecting sensors.

2. Chatbots

Enterprise AI chatbot solutions, based on NLP, have become an integral part of any organization providing customer support.

3. Enterprise Decision Management

Powered by the data-analyzing components of enterprise AI, EDM software analyzes huge amounts of data from multiple systems within an organization and helps make data-driven decisions.

4. Voice Assistants

By converting human languages into text, analyzing commands with NLP algorithms, and giving automated responses, voice assistants have become one of the ideal applications of AI in business.

5. Spam Filters

Big companies like Gmail actively use AI spam filters that detect and block junk emails to provide secure access to content.

6. Facial Recognition

The credit for facial recognition solely goes to AI. Companies can use this feature in mobile phones, laptops, and PCs for access control, employee tracking, and security protection.

Our AI Development Services Will Lead the Way to Greater Efficiency and Profitability for Your Business

Sounds Good, Let’s Begin

Benefits of Enterprise AI Solutions

Interestingly, the enterprise AI architecture comes with a high satisfaction rate among enterprise leaders, as the majority of them have acknowledged the benefits of deploying AI software in different areas:

Benefits of Enterprise AI Solutions

Pretty inspiring figures, right? Let's understand the reasons behind them:

  • With machine learning, companies can automate and optimize processes. This saves countless hours of manual labor, increases efficiency, and reduces costs.
  • Service and product innovation comes from data-driven insights into customer sentiments, feedback cycles, etc.
  • Using recommendation engines and targeted personalization, AI software systems can help you deliver an enhanced customer experience and improve your brand image.
  • AI and ML-based research and discovery uncover new ideas, methodologies, and formulas which can result in breakthrough solutions.
  • Another key advantage of using enterprise AI systems is to keep user data safe and protect digital assets from malicious attacks. This leads to high-end security and compliance.

Challenges of Adopting Enterprise AI

As with any technology, organizations might face certain challenges while implementing an enterprise AI platform, as shown in the following image:

Challenges of Adopting Enterprise AI

Apart from them, take a look at a few other hurdles you might face during the course:

  • Data ambiguity due to hidden data sources and inefficient data management.
  • AI, ML, and deep learning training programs can be costly. Companies often need external resources to execute enterprise AI projects.
  • AI-driven workflows can be complicated and time-consuming to grasp in the beginning.
  • Lack of in-house skills and expertise is a considerable roadblock for enterprise AI enthusiasts. IBM stated that 40% of workers will have to upskill in the upcoming three years to keep up with AI trends.

How to Get Started with Enterprise AI

It's critically important to come up with the right enterprise AI strategy for the maximum impact on your organization.

Having said that, we’ve jotted down a few time-tested steps to kickstart your enterprise AI project!

1. Define Your Enterprise Goals

First and foremost, understand the specific operational and business outcomes you want to achieve with AI.

  • Choose the use cases you want to target and benefit from
  • Measure the transformational impact of AI solutions on your team

2. Redefine Your Data Architecture

Data is the backbone of an enterprise AI system. You must collect and analyze all the structured and unstructured data to make it machine learning-ready and generate invaluable insights.

3. Utilize Cloud-Based Solutions

Successful enterprise AI initiatives need a comprehensive platform to keep everything running under a single hood.

Cloud is the ideal solution in that regard as it provides data analytics solutions, security tools, data storage, computing power, and so on.

4. Empower Your Team

More than the tools and systems, having the right resources and manpower to adopt and operate AI-driven solutions is essential. For that:

  • Set up a cross-functional and collaborative team including but not limited to the Chief Analytics Officer, ML developers, subject matter experts, and data scientists.
  • Create an inclusive process that integrates the final output with core enterprise operations. It should also align team members with all the stakeholders.
  • Fostering a positive culture is one of the essential enterprise AI requirements. Your team needs to embrace AI as an integral part of the overall business ecosystem.

Most Popular Enterprise AI Platforms

Since implementing enterprise AI solutions across an entire organization is a daunting task, you can leverage one or more tools depending on the project scope, skill level, or enterprise size.

Here's the list you can choose from:

  • IBM Watson Assistant
  • Databricks
  • Oracle Digital Assistant
  • AWS SageMaker
  • OneReach.ai
  • Amazon Lex
  • Google Cloud Vertex AI

Don’t Risk Failing Behind. Digitalize Your Enterprise Now for a Better Tomorrow.

Let's Talk Transformation

Get Enterprise AI-Ready with RadixwebPeople still freak out a lot of times when we talk about integrating AI/ML solutions into a project. However, it’s high time to understand the much less scary reality.AI is the next wave of revolutionary technologies and its impact on all-scale enterprises will be far and wide. If implemented in a practical, thoughtful way, AI can augment human intelligence and empower us to work at our full potential.Radixweb is here to make it easy for you. We can make AI reliable, affordable, and accessible for your business, even for non-technical users.As an esteemed AI development company, we have an extensive track record of harnessing AI solutions in various projects, with the ultimate goal of streamlining complex workflows, leveraging data-backed insights, and giving a boost to innovation and growth.Drop us a line (or two) to begin your enterprise AI journey!

Don't Forget to share this post!

Dhaval Dave

Dhaval Dave

Verified
Verified Expert in Project management
View All Posts

About the Author

Dhaval Dave, a Operations Spearhead, and a technology enthusiast at Radixweb. He holds 16 years of experience with proficiency in PHP & frameworks, Node.js, React.js, MongoDB, AWS services, and many other technologies. He is a dynamic leader with exceptional communication skills and has a track record of delivering on-time success for global brands.