Enterprise-Grade AI Solutions Transforming Business Operations in 2024

Luke Walker
June 28, 2023

Last Update: January 2024

The business-tech landscape is perpetually transforming. It’s a relentless tide that surges ahead and leaves businesses with no choice but to adapt. Recognizing this ever-present truth is crucial for every business that aims to remain relevant and competitive in this intricate dance of evolution, adaptation, and opportunity.  

Nowhere is this trend more clearly illustrated than the meteoric rise of Artificial Intelligence (AI) at the beginning of 2024. 

What just months ago appeared as a postulated, future state now is an undeniable reality. According to Forbes, over 60% of business owners believe AI will increase productivity, and a whopping 97% believe that ChatGPT alone will boost their business. A quarter of companies have already adopted AI to make up for labor shortages, and 62% of consumers are happy to engage with AI if it improves their experience.

AI tools aren't just in-vogue technologies to woo customers and bump up price tags – they’re taking over strategic and functional roles in every operational area of the business.

AI in Operations: Transforming “Business-as-Usual”

It’s important to point out that AI’s value proposition to businesses goes beyond “optimizing” business-as-usual and present-day operations. 

AI creates wholly new ways of operating and introduces potent, new pathways to operational success.  From fully-automating routine tasks to predicting market trends, from personalized marketing to enhanced decision making, AI tools are shaping the future of business success in more ways than one.

Bottom line: AI tools offer much more than technological upgrades. They’re presenting opportunities for organizations to wholly reconfigure their business strategies, operations, and goals. We’ve only begun to see the extent to which organizations implement AI as a core driver of business operations.  

How is AI Crucial for Business Operations?

Companies have already begun incorporating AI into their core operations with multiple use cases. Let's dive into the concrete areas where AI is being used in 2024.

  • Efficiency and Automation: AI can streamline workflows and automate routine tasks, thus freeing up human resources for more strategic, thought-intensive duties. An obvious example: chatbots can handle customer service inquiries around the clock, providing quick responses and consistent service. AI-driven automations can range from simpler workflows with a few steps, to multi-team and multi-system complex workflows that drive “high stakes” functions of the business.
  • Data Analysis: Businesses generate an enormous amount of data every day, and AI can help sort through this data to uncover valuable insights, risk exposures, etc. For example, AI-powered analytics tools can analyze consumer behavior data to identify patterns and trends, which can inform marketing strategies and product development. 
  • Predictive Analytics: AI can use historical data to forecast outcomes, a vital tool for planning and strategy. For example, a retail business can use AI to forecast future sales based on past data, helping to inform inventory management and sales strategies.
  • Personalization: AI can enhance customer experience by providing personalized content and recommendations.  Streaming services like Netflix and Spotify use AI to analyze user preferences and behavior, creating personalized playlists or suggesting shows that users might enjoy.
  • Risk Management: AI can help businesses identify potential risks and take proactive steps to mitigate them. For fintechs, AI algorithms can detect fraudulent activity by analyzing patterns in transaction data, helping to protect businesses and their customers.

As companies continue to push for wider adoption, AI’s role in “business-as-usual” operations will become increasingly normalized. It's not just about staying ahead of the curve anymore – it's about using AI to draw the curve.

The following is a list of the top-tier, enterprise-grade AI tools that are helping businesses today. In this context, we mean “enterprise-grade” as an indicator of readiness to serve use cases at enterprise scale and quality. It does not mean, however, that only large enterprises are ready for these tools.

10 Enterprise-Grade AI Solutions Helping Businesses Operate in 2024

1. Google Cloud AI

Google Cloud AI is a suite of AI services that offers various tools for building, deploying, and scaling AI models. It provides solutions such as Vision AI for image recognition, Video AI for video content analysis, and Natural Language for understanding and generating human language. 

For instance, an e-commerce business can use Vision AI to categorize product images, while a media company might employ Video AI to analyze and categorize video content, enhancing their content management and recommendation systems.

2. IBM Watson

IBM Watson is renowned for its advanced machine learning capabilities. 

Watson Assistant, for example, is a powerful tool that businesses can use to build conversational interfaces into any application, device, or channel. This can be particularly beneficial for customer service departments, as it can help manage high-volume inquiries, reducing wait times and improving customer satisfaction.

3. Salesforce Einstein

Salesforce Einstein is an AI tool that brings machine learning, deep learning, predictive analytics, and natural language processing to your CRM. 

Einstein can predict sales revenue, suggest the next best action for customer service, automate task assignments, and much more. This means your sales team can focus on building relationships rather than managing data.

4. Microsoft Azure AI

Microsoft Azure AI is a comprehensive suite of AI services and cognitive APIs that businesses can utilize to build intelligent apps. 

Azure Machine Learning, for instance, is a tool that helps businesses develop, train, and deploy machine learning models. A healthcare company could use Azure Machine Learning to predict patient readmission rates and improve their care management strategies.

5. UiPath

UiPath specializes in Robotic Process Automation (RPA), enabling businesses to automate mundane, repetitive tasks. 

An insurance company could use UiPath to automate their claim processing, reducing errors and speeding up the whole process. Essentially, in any business process where conditions and rules can be defined from a set of existing conditions, UiPath’s RPA can take over and drive on autopilot, enabling teams to focus on personalizing experiences and higher value knowledge work.

6. DataRobot

DataRobot offers an automated machine learning platform for data scientists of all skill levels to build and deploy accurate predictive models. A retail business could use DataRobot to forecast demand for various products, optimizing their inventory and preventing overstock or stockouts.

7. OpenAI GPT-4

Perhaps the most well-known name on this list, Chat GPT’s performance has certainly lived up to the hype of its November 2022 release, when it onboarded over 1 million users in its first 5 days online.

OpenAI’s GPT-4 is a state-of-the-art language model that uses machine learning to produce human-like text. It can be used to write emails, create content, answer FAQs, and much more, helping businesses save time and resources in their content creation and customer support efforts.

8. Amazon AWS AI

Amazon's AWS offers a broad set of machine learning services and supporting cloud infrastructure. Services like Amazon Lex, for building conversational interfaces, or Amazon Rekognition, for image and video analysis, can be utilized in numerous business scenarios. A real estate firm might use Amazon Rekognition to analyze property images and provide detailed descriptions to potential clients.

9. RapidMiner

RapidMiner is a data science platform that provides machine learning and data preparation, making it easier for businesses to unearth valuable insights from their data. In essence, they’re using AI to democratize data science and make learnings discernible for everyone.

Churn prevention is a foremost use case. For instance, a telecom company could use RapidMiner to predict and reduce customer churn, thus improving their customer retention rates. 

10. H2O.ai

H2O.ai offers an open-source machine learning platform that makes it easy to build smart applications. H20.ai customers are supported by the platform’s global network of “Kaggle Grandmasters”, machine learning and data science experts, who act as advisers for solution development and customer success champions. 

Like all other platforms on this list, the potential use cases of H20.ai are endless. One popular example, a financial services company could use the platform to create models to detect fraudulent transactions, ensuring security, supporting compliance, and boosting reputation.

AI-Built Workflows – Business Operations on Autopilot

Taking the plunge into Enterprise Cloud AI solution development is not a small undertaking. For many businesses, incremental tests and gathering learnings is the right approach today.

With Next Matter, you can now use AI to build automated workflow templates instantly. Using the AI Builder, create a step-by-step workflow template by simply naming the industry, and entering a few details about the workflow you want to create. From there, workflow steps are auto-generated, built in Next Matter, and ready for you to customize and launch – in seconds. 

‍Smart steps are AI-powered steps that can be also included in your workflows to do things like text recognition, automatic triage, synthesize and summarize, and more.

This is a powerful way for organizations to use AI to ideate, create, and test automated workflows fast – saving massive time and resources on the preparatory work that goes into mapping operations workflows . Once a workflow is proven, it can then be scaled up and optimized according to the business requirements and learnings generated.

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About the author
Luke Walker is the Product Marketing Manager at Next Matter. He is a longtime process hacker, and writes about marketing, business digitization, leadership, and work-life balance. When he's not at work, you can find him listening to records or climbing rocks.

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