AI solutions for business

AI solutions to change your business

AI solutions for business offer practical and efficient ways to enhance operations, streamline processes, and make informed decisions. By integrating AI, businesses can automate routine tasks, analyze large volumes of data quickly, and improve customer experiences. These solutions help companies stay competitive by adapting to changing market conditions and offering innovative products and services. AI is transforming the way businesses operate, making them more agile and responsive to their customers’ needs.

Putting AI to work across your business

Think about how you want to change your business. Do you want to reduce operating costs to improve margin? Scale personalized experiences to delight your customers? Create completely new revenue streams by leveraging AI-powered insights? While we recognize that not everyone shares the same immediate business priorities, speed is a universal KPI that we’re prepared to deliver. Artificial intelligence is what makes it possible.

Solutions.AI is Accenture’s collection of AI solutions that are designed to unlock new efficiencies and growth, enable new ways of working, and facilitate game-changing innovation—3x faster than the typical product life cycle. Built and delivered on the foundation of Accenture’s unparalleled AI expertise, data services, intellectual property and ecosystem partners, our scalable, modular solutions minimize time to market and maximize business impact.

Even better, while every solution is already fine-tuned for a specific industry and function, each can be quickly tailored to solve unique client challenges. So, no matter whom we’re partnering with across the organization or what we’re working to accomplish, Solutions.AI can accelerate the pace and potential of change.

What we deliver

We build and deploy powerful AI solutions that change the way our clients work.

ai solutions for business

Speed to value

We quickly configure and deploy solutions using pre-built, pre-integrated AI and machine learning (ML) models and real-time, industry-specific data sets. We scale swiftly and confidently, knowing Responsible AI must be baked in from the start.

ai solutions for business

Rapid innovation

We create and update every solution with unique Accenture IP to supercharge co-innovation with clients. And we use AIP+ to experiment and quickly prove value before we scale.

Client-first flexibility

Our solutions are AI-powered and built to deliver client value, period. That’s why they’re built to work with virtually any technology partner and used through a variety of consumption models and hosting environments, based on the specific client need.

In an era where technology drives progress, Artificial Intelligence (AI) emerges as a pivotal force in reshaping the business landscape. The integration of AI into various business processes is not just a trend but a substantial shift towards smarter, more efficient operational models. Worldwide, spending by governments and businesses on AI technology will top $500 billion in 2023, according to IDC research. But how will it be used, and what impact will it have? This guide delves into ten advanced AI solutions that are revolutionizing the way businesses operate, providing them with a competitive edge in today’s fast-paced market.

10 Advanced AI Solutions Transforming Modern Businesses: A Comprehensive Guide

1. Predictive Analytics for Enhanced Decision-Making

Predictive analytics stands at the forefront of AI applications in business. By harnessing vast amounts of data, AI algorithms predict future trends and behaviors, enabling companies to make proactive, knowledge-driven decisions. From forecasting market demands to identifying potential risks, predictive analytics is transforming the decision-making process in businesses across industries. In fact, nearly half of supply chain leaders increased spending on innovative technologies and systems during the pandemic — including predictive analytics.  

2. AI-driven Customer Relationship Management (CRM)

AI has redefined CRM systems, making them more intelligent and responsive. Integrating AI into CRM tools enhances customer interactions, automates tasks, and provides insightful data analytics, leading to more effective sales strategies and improved customer service.  

Benefits in Sales, Marketing, and Service 

A new survey of business leaders by PWC in the US shows that 88% struggle to capture the value from their technology investments.  AI-driven CRM systems offer substantial advantages in personalizing customer experiences, streamlining marketing campaigns, and providing efficient customer service. These benefits translate into higher customer satisfaction and loyalty, which are crucial in today’s competitive business environment.

3. AI in Publishing

AI technologies are playing a crucial role in automating content creation, enhancing content management, and streamlining the editorial process. By leveraging natural language processing and machine learning algorithms, AI tools are capable of generating initial drafts, suggesting content improvements, and even curating personalized content for specific audiences. The integration of AI into publishing workflows leads to increased efficiency and accuracy.

4. AI-Powered Learning Management Systems (LMS)

In the realm of education and corporate training, AI-powered LMS are proving to be game-changers. These systems offer personalized learning experiences and efficient management of educational content, benefiting both learners and educators. 

AI-powered LMS transforms corporate training by providing customized learning paths, predictive analytics on employee performance, and efficient content management. This leads to more effective training programs and a better-skilled workforce.

5. AI-Powered Cybersecurity Solutions

As cyber threats become more sophisticated, AI-powered cybersecurity solutions are essential for protecting business data and systems. AI algorithms can detect and respond to security threats in real-time, significantly enhancing an organization’s defense mechanisms. 

AI’s role in cybersecurity is pivotal, as demonstrated by Darktrace during the Tokyo Olympics. They used AI to detect and thwart an attempted cyberattack a week before the event. This incident showcases AI’s capability in early threat detection and rapid response, enhancing digital security. Such AI tools are crucial in modern cybersecurity strategies, offering advanced solutions against sophisticated cyber threats.

6. Intelligent Process Automation (IPA)

IPA represents the next level of automation, combining traditional automation with AI capabilities. This integration results in systems that can learn, adapt, and make decisions, significantly improving business processes. 

By implementing IPA, businesses achieve greater operational efficiency, reduced costs, and enhanced productivity. IPA systems automate complex tasks, streamline workflows, and provide insights for continuous process improvement.

7. AI in Talent Acquisition and HR Management

AI is revolutionizing the field of human resources, particularly in talent acquisition and management. AI tools help in screening candidates, predicting employee success, and enhancing employee engagement strategies.

8. Advanced Business Intelligence Tools

Advanced AI-driven business intelligence (BI) tools offer deeper insights into business data compared to traditional BI tools. These AI tools analyze complex datasets to uncover patterns and insights that drive strategic decision-making. 

The comparison between AI-powered BI tools and traditional ones highlights the enhanced capabilities of AI in processing and interpreting large volumes of data, providing businesses with actionable insights for growth and innovation.

9. AI in Financial Analysis and Forecasting

In the financial sector, AI plays a critical role in analysis and forecasting. AI algorithms can process vast amounts of financial data, predict market trends, and assess risks, aiding in better financial decision-making. 

Banks and financial institutions are increasingly adopting AI for credit scoring, fraud detection, and investment analysis. These applications demonstrate AI’s potential in enhancing accuracy and efficiency in financial services.

10. Sustainable Business Practices Through AI

AI contributes significantly to sustainable business practices. By optimizing resource use and improving operational efficiency, AI helps businesses reduce their environmental footprint. 

AI applications in energy management and waste reduction are prime examples of how technology can aid in achieving sustainability goals. Companies are using AI to optimize energy consumption and minimize waste, contributing to a more sustainable future. For example, computer vision is used in conjunction with satellite imagery to identify deforestation and illegal logging activity in the rainforests, as well as illegal fishing activity, which impacts biodiversity in the oceans. 

The transformative power of AI in business is undeniable. These ten advanced AI solutions offer a glimpse into a future where technology and innovation drive business success. As businesses continue to evolve, the adoption and integration of AI will be key to staying competitive and achieving sustainable growth.

15 top applications of artificial intelligence in business

The use of artificial intelligence in business is now mainstream, with many organizations implementing AI as a standalone technology for specialized use cases or embedding it within common enterprise software systems that handle core business processes.

Investment in AI continues apace. A March 2024 pulse poll of 250 technology leaders by professional services firm EY found that 82% of tech business leaders plan to increase their AI investment in the next year. Nearly two-thirds (64%) of respondents said their company had instituted internal development programs to help employees keep pace with the rapidly evolving features of generative AI, and 76% said their companies also have internal certification programs in generative AI for employees.

While the executives surveyed by EY had concerns about the difficulty of hiring AI talent and expressed the need for more AI regulation, they were largely positive about AI in their organizations: 72% said their employees are using AI at least daily in the workplace. The top use cases were coding and software development, data analysis, and internal and external communication.

We interviewed AI experts and practitioners on how companies are applying AI. Here are 15 top applications of artificial intelligence in the enterprise.

This article is part of

1. AI-enabled innovations, products and services

Although organizations are only beginning to harness the potential of artificial intelligence, some are already using the technology to fuel innovation and create new products and services.

While virtual assistants are some of the most well-known examples, industries are finding many other ways to incorporate AI into their wares or use AI to develop new offerings.

As an example, Seth Earley, author of The AI-Powered Enterprise and founder and CEO of Earley Information Science, pointed to a company using AI to improve its telecommunications platform. The organization is also employing machine learning and other AI technologies to improve the quality of the speaker’s voice and image and to keep the images of others participating from becoming distorted on screen.

Brian Jackson, principal research director at Info-Tech Research Group, highlighted a retailer that’s collaborating with artists to feature their designs on clothing, using AI to develop the art and manufacturing merchandise to order.

2. Automating routine cognitive work

Organizations for years have used AI to automate many manual tasks, such as data entry. Now they’re using next-generation intelligence, such as generative AI, to handle cognitive tasks such as summarizing reports and drafting communications.

“AI is now tackling some of the grind work,” said Nicholas Napp, a senior member of the Institute of Electrical and Electronics Engineers, noting that this use of AI could affect many jobs. “Much of our jobs are grind versus special experience, and AI is really good at that grind.”

3. AI for leveling up workers

Even when tasks can’t be automated, experts said AI can still aid workers by offering advice and guidance that helps them level up their performance.

Kavita Ganesan, an AI adviser, strategist and founder of consultancy Opinosis Analytics, cited Grammarly and similar services that use AI to not only catch misspellings in text but to correct grammar and offer preferred phrasings to improve a user’s writing.

Others noted that generative AI brings even more aid to workers, who with little or no experience can use the tool to write software code, design a logo or craft a marketing strategy.

Such AI applications “help level up the skills of a more junior person in the company and help them perform at a more senior level, and it helps experts really shine,” said Mike Mason, chief AI officer at consultancy Thoughtworks. “It’s an enabler that allows people to do things they otherwise wouldn’t have been able to do.”

4. AI as a creative force

Indeed, artificial intelligence is now capable of creating compositions of all kinds, including visual art, music, poetry and prose, and computer code.

Some have questioned whether AI-generated works are derivative in either the legal or artistic sense — or both — as the technology works by analyzing and learning from the data it’s given for training. Regardless of the answer, AI is being used by organizations to create a range of works.

Napp, who is also co-founder of Xmark Labs, tested OpenAI with a Moby Dick-inspired query — “As Captain Ahab, can you pretend to be a teenage TikTok influencer and tell me about your quest for the whale?” — and received an original three-paragraph narrative in response.

Napp also said he and a math teacher used ChatGPT to create real-world examples of a mathematical concept in action to inspire students, and worked with one of his children to create an adventure for the fantasy game Dungeons & Dragons.

Top enterprise applications of artificial intelligence.

Here are 15 top applications of AI in business, plus industry-specific examples of AI use.

5. Accessing and organizing knowledge via AI

Accessing and organizing knowledge is another area where AI — in particular, generative AI — is demonstrating its potential to organizations and their workers.

The technology lets workers not only search through reams of information, such as institutional files or industry-specific data, to find relevant elements, but it also organizes and summarizes those elements.

Although this application of AI is potentially transformative, Earley warned that the technology isn’t reliable enough to use without human oversight or review. AI systems, such as ChatGPT, don’t always have all the data sets needed to reach accurate and complete conclusions, he explained, and they often make assumptions that aren’t correct.

Case in point: Two lawyers in early 2023 submitted a court brief created using ChatGPT only to find the technology had fabricated some of the cases cited in the legal document.

6. AI for optimization

Optimization is another AI use case, and it’s one that stretches across industries and business functions.

AI-based business applications can use algorithms and modeling to turn data into actionable insights on how organizations can optimize a range of functions and business processes, from worker schedules to production product pricing. AI systems can use data, identify bottlenecks and offer optimized options to implement.

“Organizations can benefit from using AI for the automation of repetitive tasks, which reduces manual efforts and increases accuracy,” said Moe Asgharnia, CIO at accounting and consulting firm BPM.

7. Higher productivity and more efficient operations

Another top reason organizations are adopting AI technologies is to boost productivity and generate more efficiencies, said Sreekar Krishna, U.S. leader and head of data engineering of AI at professional services firm KPMG.

He said AI can be plugged into many processes that require human labor and then either fully or partially perform that process — faster, more accurately and at a higher volume than any human could.

8. More effective learning and training through AI

Many organizations are using or exploring how to use intelligence software to improve how people learn.

Intelligent tools can be used to customize educational plans to each worker’s learning needs and understanding levels based on their experience and knowledge. Asgharnia said that it lets organizations implement more effective training programs.

9. AI as coach and monitor

In a related application, organizations are deploying AI-powered systems that coach employees as they work. The technology, experts explained, has the capability to monitor and analyze actions in near real time and provide feedback, thereby coaching or guiding workers through the process.

For example, many logistics and transportation companies use systems featuring cameras, eye-tracking technology and other AI algorithms to monitor for distracted driving, alerting workers to the problematic behavior and offering corrective actions.

10. Decision support

A similar application of AI in the enterprise is the use of an intelligent decision support system (DSS). These systems sort and analyze data and, based on that analysis, offer suggestions and guidance to humans as they make decisions.

Doctors, accountants and researchers are among the professionals who use such software, Asgharnia said. As an example, he pointed to a DSS that helps accountants wade through tax laws to identify the most beneficial tax strategies for their clients.

11. AI-enabled quality control and quality assurance

Manufacturers have been using machine vision, a form of AI, for decades. They’re now advancing such uses by adding quality control software with deep learning capabilities to improve the speed and accuracy of their quality control functions while keeping costs in check.

These systems deliver a more precise, and ever-improving, quality assurance function, as deep learning models create their own rules to determine what defines quality.

12. AI for personalized customer services, experiences and support

Delivering personalized customer services and experiences is one of the most prevalent enterprise use cases for AI.

“It’s using identifiers about customers and consolidating signals from multiple systems to understand who they are, what describes them, [and] what motivates them to create a personalized experience,” Earley explained.

Although the use of AI for such a purpose is widespread, Earley said companies could be more effective. “I think personalization isn’t being done well today, or not at the level it can be,” he said.

Chart listing 5 AI enhancements for contact centers: IVR systems, self-service chatbots, agent performance analytics, predictive customer analytics, and post-call-chat summaries.

13. Safer operations

AI is being used by a multitude of industries to improve safety.

Construction companies, utilities, farms, mining interests and other entities working in outside locales or in spacious geographical areas are gathering data from endpoint devices such as cameras, thermometers, motion detectors and weather sensors. Organizations then feed that data into intelligent systems that identify problematic behaviors, dangerous conditions or business opportunities, and make recommendations or even take preventive or corrective actions.

Other industries are making similar use of AI-enabled software applications to monitor safety conditions. For example, manufacturers are using AI software and computer vision to monitor workers’ behaviors to ensure they’re following safety protocols.

Organizations of all kinds can use AI to process data gathered from on-site IoT ecosystems to monitor facilities or workers. In such cases, the intelligent systems watch for and alert companies to hazardous conditions, such as distracted driving in delivery trucks.

14. AI for functional area improvements

The functional areas within the typical enterprise are also putting AI to good use for their own specific needs:

  • Customer service uses chatbots powered by machine learning algorithms and natural language processing to understand customer requests and respond both faster and cheaper than human workers can. AI also powers recommendation functions, which use customer data and analytics to suggest products customers are most likely to need or want and therefore buy. Intelligent systems can help employees better serve customers by drawing on analytics, like those used in chatbots and recommendation engines, to give workers suggestions as they tend to customers.
  • Marketing uses intelligent systems to understand users and their buying patterns so they can create targeted marketing campaigns with a higher success rate than their generic counterparts. Some organizations are also combining intelligent technologies — including facial recognition, geospatial software and analytics — to identify in-store customers and promote products, services or sales that match their personal preferences.
  • The supply-chain function uses algorithms to forecast what will be needed when and the optimal time to move supplies. In this use case, AI helps business leaders create more efficient, cost-effective supply chains by minimizing and even possibly eliminating overstocking and the risk of running short of in-demand products.
  • The HR function uses AI-powered systems to help write more interesting and accurate job postings, identify and screen potential candidates, and create personalized training and development programs for employees.
  • Cybersecurity uses AI to more efficiently and effectively monitor the enterprise IT environment to detect anomalies that could indicate a cyberthreat.
  • IT can use AI systems to write and document code.
  • The C-suite and the board can use AI to identify, analyze and rate risk, helping them to create better risk management strategies.

15. AI for addressing industry-specific needs

Although many AI applications span industry sectors, other use cases are specific to individual industry needs. Here are some examples:

  • Healthcare. The healthcare industry employs artificial intelligence and machine learning products to analyze the vast troves of data collected over recent decades to uncover patterns and insights that humans aren’t able to find on their own. Algorithms in diagnostic tools are helping clinicians make more accurate diagnoses earlier in a disease’s progression. Other intelligent tools help clinicians develop more individualized treatment plans designed for maximum efficiency for each patient.
  • Financial services. The financial services sector uses AI and machine learning for fraud detection, digital and data security, and to analyze historical and real-time data to make near-instantaneous decisions about the legitimacy of individual transactions. Financial services firms also use AI for more niche applications, such as wealth management, loan approvals and trading decisions.
  • Industrial maintenance. The industrial sector uses AI for predictive machine maintenance to identify the most probable time equipment will need service and to optimize the scheduling of maintenance work. AI is also used in factories to increase efficiency.
  • Transportation. AI is enabling a growing fleet of self-driving vehicles that are becoming smarter as they gain navigation experience. AI is also being used for smarter traffic management operations and transportation logistics.

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