AI in digital transformation: 10 examples of artificial intelligence in action
July 15, 2026 15 min read 267 views
Empowering digital transformation with AI: insights, examples, and strategies for success.
Businesses are innovating to stay relevant, and digital transformation has become a key part of this journey. But as organizations rethink their traditional models and processes, many are turning to artificial intelligence (AI) to accelerate change. According to PwC’s 2026 AI Performance Study, companies achieving the strongest financial results from AI are 2.6 times more likely to use the technology to reinvent their business models and twice as likely to redesign workflows around AI rather than simply add new tools.
AI is also becoming a growing priority for business leaders. Forbes found that 95% of organizations plan to increase investment in AI and cybersecurity in the year ahead, highlighting how essential these technologies have become for future growth.
So, how exactly can AI support your digital transformation strategy? Let’s explore 10 real-world examples of AI-powered solutions and see how businesses use them to improve processes, make smarter decisions, and create better customer experiences.
How businesses boost digital transformation initiatives with artificial intelligence and machine learning
AI supports digital transformation by helping businesses automate processes, uncover insights from data, and improve how they operate and serve customers. By combining machine learning, predictive analytics, and pattern recognition, AI enables organizations to optimize workflows and make more informed decisions.
Organizations have come to rely on AI tools to improve their processes and business models. So, let’s look at how they use AI for digital transformation today.
Generative (computational) design
AI-powered generative design can transform product development by helping engineers explore and evaluate multiple design options based on specific requirements. By analyzing parameters such as dimensions, materials, weight, and performance goals, AI systems can generate alternatives that allow teams to optimize designs faster and make more informed decisions.
AI adoption in product development is accelerating as engineering teams look for ways to improve design workflows and create more efficient products. According to Avnet’s survey, 82% of respondents said they have products or are working on new designs that feature AI, highlighting how embedded these technologies are becoming in modern engineering processes.
Companies are also applying AI beyond initial design stages to optimize manufacturing and product lifecycles. For example, Rolls-Royce uses AI and machine learning to improve engineering and manufacturing operations, including optimizing processes, monitoring equipment performance, and predicting potential maintenance issues before they cause disruptions.
Personalized offerings
AI-powered engines can help you tailor the customer experience. Think about the vast amount of data you have about your customers: location, purchase history, search inquiries, preferences, social media activity, and other metadata. AI software can process this information to identify patterns, understand customer intent, and provide more relevant recommendations for different types of travelers.
AI-driven personalization is becoming an important part of the travel and hospitality experience. According to Booking.com’s Global AI Sentiment Report, 67% of travelers have already used AI during their travel journey, with nearly all of them using it for planning or booking trips. Travelers are mainly turning to AI for destination research, local experience recommendations, and other personalized travel suggestions.
Travel companies are already using these capabilities to improve how customers discover and book services. Booking.com uses machine learning to anticipate users’ destinations and recommend relevant hotels based on their preferences and behavior. Similarly, Red Roof Inn used AI-based analytics to monitor real-time flight cancellation data and optimize mobile search campaigns around affected airport locations, increasing conversion rates by 375% in those areas.
Robotic process automation
Robotic process automation (RPA) helps companies automate repetitive workflows, reduce manual effort, and improve process accuracy. When combined with AI, RPA can handle more complex tasks by processing information, identifying patterns, and supporting faster business decisions.
AI-powered automation is becoming increasingly important in banking, where financial institutions use it to streamline operations, improve customer service, and optimize compliance processes. According to EY India’s research, generative AI could improve productivity in banking operations by up to 46% by 2030 by supporting areas such as workflow automation, customer service, and business processes.
Automation is especially valuable for financial institutions that often deal with time-consuming workflows such as customer onboarding, compliance checks, and document processing. For example, Mauritius Commercial Bank used AI, intelligent document processing, and automation to modernize its customer onboarding process, reducing onboarding time by 64%, from 70 minutes to 25 minutes, while improving document accuracy and compliance transparency.
Claims automation in insurance
Insurance companies can accelerate their digital transformation initiatives with AI, RPA, and data analytics. These technologies allow insurers to streamline claims processing, automate manual workflows, detect fraud more effectively, and deliver faster customer experiences. According to NTT DATA’s Global AI Report, 86.7% of insurance AI leaders use AI in back- and mid-office workflows for automation and optimization, highlighting how operational automation has become a key focus for insurers.
AI-powered claims automation can reduce administrative workload and accelerate decision-making. For example, IBM helped a leading insurance claims administrator modernize its claims process using AI and automation, increasing employee productivity by 20x, making claims cycles four times faster, and increasing processing capacity from 15 claims per day to up to 288.
Supply chain optimization
AI-based demand forecasting models, business planning tools, process optimization, and predictive maintenance are transforming supply chain management. By analyzing large volumes of operational data, AI can enable companies to improve logistics, optimize inventory levels, and respond more quickly to changing demand patterns.
Organizations that have adopted AI in supply chain operations have reported improvements across multiple areas, including up to 15% better logistics performance, 35% lower inventory costs, and up to 65% improvements in service performance. Additionally, many executives report revenue growth after implementing AI solutions across supply chain processes.
AI is also being applied to improve warehouse operations and inventory management. For example, C3 AI provides AI-powered supply chain solutions that give warehouse managers real-time inventory insights and stock recommendations. The company reports that its software can help reduce shipping costs by 20–50% and lower inventory levels and holding costs by 15–30%.
Drug discovery
The recent advancement spurred by COVID-19 led the market of AI in drug discovery to grow from $259 million in 2019 to $10.93 billion by 2031. Biotechnology and pharmatech companies actively use algorithm-based software to reduce the time and resources needed to develop drugs.
Exscientia says that its AI platforms helped reduce the traditional discovery process for a drug candidate from five years to eight months. The world’s largest corporations, like IBM, Microsoft, and Google, are also heavily investing in AI solutions and drug discovery providers.
AI digital assistants and chatbots
Companies use AI-powered assistants to provide round-the-clock customer support and enable support agents to handle tickets more efficiently. Deloitte’s research found that 43% of organizations expect AI to reduce contact center costs by 30% or more within three years, while 64% of service leaders report higher agent productivity from AI. According to Gartner, 91% of customer service and support leaders are under pressure from executives to implement AI, highlighting the growing focus on AI-powered service operations.
Other companies invest in more advanced digital assistants. One such technology is Google Duplex — an automated appointment booking and scheduling system that lets you interact with any business listed on Google. However, a system capable of recognizing complex sentences and fast speech must include technologies like natural language processing (NLP).
Natural language processing
NLP allows the software to understand a language’s context and emotional background. You’re probably familiar with its capabilities, including speech recognition, automatic translations, predictive typing, word filters, and digital assistants.
These technologies are widely used in healthcare to automatically extract, structure, and classify medical records and handwriting. This research suggests that NLP can facilitate policy assessments and decrease the time needed for clinical guideline synthesis.
On top of that, NLP can be used for sentiment analysis. For example, some software can scan and evaluate reviews about your company on social networks. Expedia Canaday used sentimental analysis to detect negative feedback about its ad campaign and ditch it before any damage was done.
Cybersecurity and fraud detection
The average cost of a data breach continues to rise, reaching $4.44 million globally in 2025, according to IBM’s Cost of a Data Breach Report. The same research highlights that organizations using AI and automation in their security operations can detect and contain incidents faster, reducing the overall impact of breaches. This shows why AI-powered security has become increasingly important for businesses handling sensitive data.
AI-powered software uses real-time analytics and historical data to detect user behavior discrepancies. So, your system can automatically block login attempts from unusual locations, suspicious transactions, or large cash withdrawals.
Because of fraud, travel, and transportation companies suffer billions of dollars in losses annually. Thankfully, AI and machine learning can help you protect your transactions. For example, HotelTonight reduced chargebacks by 50% after deploying an AI solution for fraud detection.
Employee monitoring
Many companies started buying AI-powered monitoring tools as remote and hybrid work models prevailed over on-site work. When used appropriately and according to data protection frameworks, this approach helps quantify factors for employee productivity. But there are other ways to use these tools.
Research states that organizations with over 60% of the remote workforce have higher data breach costs. Companies with an 80-100% remote workforce suffer about $5.54 million from breaches, compared to an average of $4.24 million. However, advanced AI monitoring software can help prevent malicious insider threats like corporate espionage and intellectual property theft.
Even in its current form, AI has immense digital transformation power. Above all else, it can innovate your business.
Benefits of artificial intelligence among digital transformation examples and strategies
AI can accelerate digital transformation by improving operational efficiency, supporting better decisions, reducing costs, and creating more personalized customer experiences. The examples above show how organizations across industries use AI to automate processes, analyze data, and adapt their business models to changing demands.
Let’s look at the key benefits AI can bring to your organization.
Productivity boost
AI tools like RPA and NLP can help businesses automate complex processes, reduce human error, and free employees from redundant tasks. According to Statista report, AI can enhance labor productivity in developed countries by 40% by 2035 (with Sweden, the US, and Japan benefiting the most).
The same report illustrates that 76% of employees with disabilities aren’t fully open about them. Luckily, advances in accessibility software (speech-to-text, predictive typing, visual recognition, and others) might help them eliminate some of these barriers so that they can focus on their job.
Cost-efficient processes
Adopting AI initiatives helped organizations reduce their expenses while simultaneously increasing revenue.
McKinsey’s State of AI report shows that 39% of respondents reported cost reductions from AI use cases, while 32% reported revenue increases in the business functions where AI was implemented. These results demonstrate how organizations are using AI to optimize operations and improve financial performance.
AI-powered analytics can further improve cost efficiency by identifying inefficiencies, optimizing resource allocation, and reducing manual operational work. According to Deloitte, 66% of organizations have already achieved productivity and efficiency gains from enterprise AI adoption, while 40% reported cost reductions.
Informed decision-making
Predictive analytics software enhances your business decisions’ quality, creativity, and effectiveness. AI applications process large quantities of unstructured data from multiple sources and turn it into insights. This helps uncover gaps between your offerings and demand and introduce the services your clients want.
Analyzing data in real time is critical for actionable corrective actions. Take automotive IoT, where autonomous vehicles must respond to external objects and safety scenarios in milliseconds, or cybersecurity, where you need to react to intrusions immediately.
Client-centric business model
Automated self-service tools, digital assistants, and chatbots can help your customers solve their problems seamlessly, keeping them happier. According to Deloitte’s The State of AI in the Enterprise report, enterprise executives cite improved and better customer service and satisfaction as their primary reason to invest in AI.
AI-based algorithms and Big Data help companies develop detailed customer behavior profiles to understand their needs, problems, and preferences. With this data, you can tailor ad campaigns and interfaces for user segments, likely improving customer satisfaction.
Still, despite all these benefits, many companies need to be more cautious about the upfront costs of AI. That’s why you need to consider what business aspects of your organization could use an AI boost.
What business aspects should you enhance with AI?
The most valuable areas to enhance with AI are the processes where automation, data analysis, and predictive insights can create measurable business impact. Choosing the right AI initiatives is essential for successful digital transformation, as scalable solutions can deliver greater value across your organization.
88% of senior managers and executives believe they won’t achieve their growth objectives without scaling AI—however, 76% struggle with rising algorithm-based tech across their businesses.
What AI directions should your company choose, and how to successfully implement them at ai projects and scale?
Define the processes to improve
Start by assessing your IT infrastructure, internal policies, and workflow. This should give you a good idea about the most value-driven processes in your company. The audit also helps to pinpoint bottlenecks in your chain of operations. For example, it could be an overly complex onboarding process, invoice management, or slow customer service.
Then, you must select the processes you can enhance or automate with AI. However, it would help if you didn’t spread too thin across all your various business operations. Algorithm-based technologies can be pretty expensive. We recommend prioritizing the operations you could improve with minimal investments.
Optimize your workforce
Your employees need to understand how AI applies to their roles, so redefining your organization’s responsibilities and ways of working is imperative. You must also train your staff with new tools and security practices.
It’s important to distinguish the roles of AI practitioners and data scientists. Data officers, modelers, and machine learning engineers must uphold clear standards, rules, and processes to bring value to your business. Besides, vetted data science practitioners can apply new technologies across use cases with consistent results, improving your value from AI investments.
Establish cybersecurity and governance
Cybersecurity is detrimental to your reputation and financial well-being. You need to embed security mechanisms into your AI solutions and ensure compliance with privacy regulations laws (GDPR, PCI DSS, HIPAA, to name a few).
You also need to address the ethics problems. For example, algorithms can discriminate based on gender, race, socioeconomic factors, disabilities, or other conditions. This could lead to biases and, consequently, unreliable results. So, it would help if you had a transparent governance network to ensure the ethics code is correctly translated into the development.
Gather enough data
AI and machine learning systems need a large amount of data to provide accurate results. So, smaller businesses need to collect enough information before their deep learning platform can produce reliable insights.
You also need to understand that most data is useless for strategic decisions. Aside from that, terabytes of useless files only clutter your storage and increase the system’s workload. That’s why you need software and policies to filter through low-quality, duplicate data and other issues (like misspelling in user profiles).
Using AI to automate redundant tasks is effective but has a limited impact on your digital transformation journey. It would help if you had the right strategy to leverage the potential of AI systems to the fullest, and that’s possible with an experienced partner on your side.
FAQ
Final remarks
Businesses that want to digitalize should know what processes are worth upgrading, the digital technologies they must implement, and the organizational processes to optimize to make it all work. This requires a team of experienced specialists, access to a digital tech stack, and knowledge of management procedures.
Artificial intelligence boosts digital transformation across industries. AI can profoundly affect your business by allowing you to automate tasks, personalize offerings, improve customer satisfaction, and mitigate risks.
We have the knowledge and experience to implement AI technologies and reimagine your business processes to make your business more cost-efficient, consumer-centric, and profitable. Reach us to see how we can accelerate your digital transformation.
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