Top 7 Enterprise AI Implementations in 2023

The integration of artificial intelligence into the corporate landscape is fundamentally reshaping business practices. Enterprises are integrating AI solutions into their operations to achieve cost savings, enhance efficiency, uncover valuable insights, and explore novel markets.

 

In fact, the AI market, which was valued at $150.2B in 2023, is expected to grow to $1,345.2B by 2030. It is expected to grow at a CAGR of 36.8%. And enterprises, including Fortune 100, are seeing it.

 

AI-driven enterprise applications span a spectrum of functions, from improving customer service and amplifying sales efforts to fortifying cybersecurity measures, streamlining supply chain management, liberating employees from repetitive tasks, refining current product offerings, and illuminating pathways to innovative products, and most importantly, improving decision making.

 

It's challenging to identify a facet within the corporate domain that won't be touched by AI – the replication of human processes by machines, particularly computer systems – leaving its mark.

 

Well, there are endless possibilities and we’re still scratching the surface of AI. But, in order to understand how the market is responding to AI, we need to understand the real-world implementations that are happening at the enterprise level.

AI and big data work closely together in today's business world. Businesses gather a lot of data, which can be a mix of different types like organized, unorganized, and partially structured information. This data serves as the foundation for getting detailed insights and analyses that help businesses improve their operations and discover new opportunities. However, making sense of this vast data requires the power of AI.

 

For example, AI techniques like deep learning are used to process huge amounts of data and find hidden patterns and connections that can give companies a competitive edge. These insights might not be obvious through traditional methods. So, AI helps businesses uncover valuable information from their data, leading to better decisions and a stronger position in the market.

 

In the same context, enterprises are heavily investing in AI to realize the next wave of technological disruption and operational efficiency.

 

Here are the top 7 AI implementations top companies are experimenting with in 2023:

Cisco recently introduced a new feature that uses smart technology to help people catch up on things they missed during online meetings and calls on their platform called Webex. This feature quickly summarizes what was discussed in the meeting so users can quickly understand what happened. It can also help users find important parts in videos and understand long chat messages. Another cool thing is that it can automatically make a summary of a meeting, highlighting important points and things that need to be done.

 

 

Source: Webex

 

Cisco is also using this smart technology to improve the security of their products. They're making it easier for people to manage security rules and respond to threats.

 

Why this is interesting is because Cisco, even though they've been looking at smart technology for a while, is now using it in their products for the first time. These new features will make their platform easier to use and help people get more work done. A study by Cisco found that many tech experts believe this kind of smart technology will have a big impact on businesses. So, Cisco is using it to make meetings better and work more productive.

 

As someone who uses video calls a lot to collaborate with clients for their chatbot development company, I really appreciate how this could save time by automatically keeping track of what's said in calls. These features could make Cisco Webex stand out in this type of software.  

Dell and Nvidia joined forces for something called Project Helix. It's about making it easier for companies to use smart technology to create useful things. The main goal is to help businesses, big and small, use smart technology that can make things like computers smarter.

 

 

Source: TECHGOING

 

Project Helix has different parts, like designs that are already tested, special computers that are great for smart tasks, and storage for data. They also have a way to monitor everything using a cloud service, which is like a tool to keep track of things.

 

This project is interesting because it helps companies use smart technology without sharing important stuff on the internet. Keeping everything in-house is safer. Project Helix is a good way for companies to make their own smart programs and tools. They can use their own data to get better results, which is important. It's like making sure what they create is unique and useful. Also, this way they can avoid problems that come from using data that's available to everyone.

HPE has launched a cloud service called HPE GreenLake for LLM. It's like a cloud service for using smart technology to work with language and images. They partnered with a company called Aleph Alpha to make this possible. They want to help with things like climate modeling and healthcare.

 

 

Source: HPE GreenLake

 

What's special is that this service is like a super-powerful computer that companies can use whenever they need it. This is great for handling a lot of data, which is important for smart programs. Plus, they don't charge extra for moving data around, which is different from many other similar services.

 

Another good thing is that they provide experts to help companies use this service well. They can help make sure everything works as it should and that the programs get the best results.

 

And the best part is that you can access this powerful computer from anywhere using the internet. This makes it easy for teams to work together even if they are far away from each other.

Lenovo wants to make it easy for companies to use smart technology everywhere. They have a big group of partners and together they offer lots of ready-to-use smart solutions for different things like recognizing images and sounds, making predictions, and improving security. They've invested a lot of money to make this happen. And recently, they’ve announced an investment of $1 billion over the next three years for AI initiatives.

 

 

Source: TechObserver

 

Lenovo is significantly broadening its range of AI-compatible infrastructure, featuring a collection of more than 70 products, including fresh AI-focused edge-to-cloud server platforms. The latest addition to this expansion is the Lenovo ThinkEdge SE360 V2, an advanced edge server that provides increased processing capability to support various AI applications, encompassing computer vision, voice AI, and generative AI.

 

Lenovo is smart because they understood early on how important smart technology is. They've been working on it for a long time and they're planning to spend even more money to make even better solutions in the future.

AmEx has taken note of the recent emergence and growing excitement surrounding AI products such as OpenAI's ChatGPT, Google's Bard, and Anthropic's Claude – all built upon large language models. Recognizing this trend, the company envisions a promising opportunity to employ these technologies to enhance customer experiences within their credit card and banking services, both for individuals and businesses.

 

AmEx's involvement in AI predates its widespread adoption as a major trend. In 2017, the company established AmEx Digital Labs, a specialized division with the innovative spirit of a startup. With a global team of 100 skilled technology experts, this division has been at the forefront of utilizing AI for financial services.

 

An illustrative achievement was the successful integration of Mezi, an AI-powered digital assistant focused on travel recommendations, into an experimental AmEx mobile app program. The positive outcomes from this pilot prompted AmEx to acquire Mezi's developers and integrate its advanced technology across its services.

 

AmEx Digital Labs is now actively exploring the potential of generative AI to enhance predictive analytics capabilities, aiming to gain deeper insights into customer behaviors and patterns. The core objective is to improve financial planning and decision-making by predicting customer performance over time.

 

Moreover, AmEx aims to apply AI in customer sentiment analysis and to enhance customer interactions. The company's AI strategy revolves around enhancing the overall customer experience and providing innovative solutions to simplify their lives.

In April of this year, Atlassian unveiled its latest offering – Atlassian Intelligence – incorporating cutting-edge generative AI capabilities into its suite of cloud-based workforce management products. These capabilities are geared towards enhancing efficiency for both service-based and project-based teams.

 

Atlassian Intelligence is the result of merging in-house AI models, acquired through the purchase of Perceptive.ai in 2022, with a partnership involving Microsoft-backed OpenAI, the creators of ChatGPT.

The platform offers several ways to support teams, including expediting workflow, providing instant assistance, and fostering improved collaboration on projects.

 

The generative AI technology from OpenAI is utilized in Atlassian Intelligence to efficiently generate, summarize, and extract information from diverse content sources. For example, meeting minutes can be succinctly summarized to highlight decisions and action items, while tweets can be composed using information stored in Confluence.

 

While ChatGPT technology contributes to handling natural language requests for Atlassian Intelligence, it's essential to note that Atlassian has a stipulation in place to ensure that neither customer data nor sensitive information will be retained by the software or OpenAI. This commitment ensures the privacy and security of users on the platform.

In July of the present year, Salesforce officially introduced Service GPT, Sales GPT, and the Einstein GPT Trust Layer – offerings aimed at boosting productivity and delivering personalized customer interactions through generative AI. These solutions are meticulously designed to adhere to stringent enterprise security standards.

 

Service GPT empowers users with auto-generated personalized responses and automated summaries of customer interactions for future reference.

 

Sales GPT empowers users to craft personalized customer emails using AI, drawing from contextual data stored within Salesforce.

 

The Einstein GPT Trust Layer guarantees that customer data remains confined within Salesforce and is not retained or utilized by third-party large language model (LLM) providers for prompts or responses. This approach underscores the emphasis on data security and privacy.

 

Salesforce AI's CEO, Clara Shih, underscored the approach's open ecosystem and reliance on real-time proprietary data to power the generative AI features, permitting organizations of varying sizes to harness AI's productivity and efficiency benefits while maintaining a robust foundation of trust and data security.

AI, particularly narrow AI like deep learning and machine learning, has made a significant impact across various industries. Major tech companies such as Google, Microsoft, Apple, and Amazon are heavily investing in AI-driven products and services. Andrew Ng, a prominent AI expert, envisions a continuous era of AI advancement. Different industries are embracing AI in diverse ways:

AI is making a significant impact on the IT industry with several possibilities:

 

- Automation: AI is streamlining complex IT operations, automating tasks, and increasing efficiency. It allows IT professionals to focus on strategic activities by handling mundane tasks.

 

- Security Enhancement: AI plays a critical role in IT security by utilizing machine learning algorithms to monitor patterns and detect anomalies in real time. This proactive approach helps prevent potential cyber threats.

 

- Data Management: AI algorithms enable quick processing and analysis of large data volumes, enhancing decision-making speed and overall efficiency in data management.

 

- Predictive Maintenance: AI aids in predicting and preventing potential IT issues, reducing downtime and associated costs for businesses.

 

- Customer Service: AI-powered chatbots improve customer service by managing routine inquiries, freeing up IT teams to address more complex customer issues.

 

- Software Development Transformation: AI is revolutionizing software development with more efficient coding practices and faster application deployment. Automated testing using machine learning predicts and corrects bugs, speeding up the development cycle and improving software quality.

 

- System Integration: AI assists in system integration by learning the behavior of different software systems and suggesting effective integration approaches, saving time and resources.

AI is aiding manufacturers in overcoming challenges like high costs, inflexible production lines, and quality control. Solutions include Robotic Process Automation (RPA) for repetitive tasks, digital twins for lifecycle monitoring, machine learning algorithms for demand forecasting, and automated inspection tools for defect detection. The AI adoption rate is high, with 93% of manufacturing companies recognizing its importance for growth. The market for AI in manufacturing is projected to reach $60 billion by 2022.

A significant portion (56%) of businesses are using AI in various functions. AI is employed for enterprise knowledge management, lead automation, robotic process automation, and customer service through natural language processing (NLP) and machine learning. It's versatile and can be integrated across sales, marketing, security, and other processes.

The AI healthcare market is anticipated to surpass $95 billion by 2028. AI addresses labor shortages and supports healthcare professionals. Applications include personalized medications, drug discovery, fraud detection, virtual nursing assistants, and even AI-assisted robotic surgeries. The robot-assisted surgery sector could be worth around $40 billion by 2028.

The finance and banking industry is leveraging AI for real-time transaction monitoring, customer onboarding with biometrics, regulatory compliance analysis, financial product recommendations, and cybersecurity and fraud detection. Machine learning enhances customer experiences and identifies new risk management opportunities.

AI's impact is not limited to the industries we’ve talked about so far; it's also evident in education, accounting, sales, transportation, retail, and more. The integration of AI across diverse sectors showcases its transformative potential.