AI has become the backbone of digital transformation, helping businesses modernise legacy systems, automate workflows, reduce risks, and unlock new revenue opportunities across all industries.
It improves customer experience through hyper-personalisation, allowing companies to understand user behaviour, deliver tailored recommendations, and run adaptive, high-impact marketing campaigns.
AI speeds up decision-making with powerful data analysis, enabling organisations to predict trends, detect risks early, and make informed choices—whether in healthcare, finance, retail, or product development.
Core AI technologies like NLP, computer vision, predictive analytics, generative AI, and autonomous systems help businesses streamline operations, automate repetitive tasks, enhance accuracy, and boost productivity.
Across sectors—healthcare, banking, ecommerce, education, logistics, and product development—AI creates new value, from fraud detection and smart pricing to personalised learning and early disease diagnosis.
Overall, AI is no longer optional; it is a strategic necessity for companies aiming to innovate faster, operate smarter, and stay competitive in 2025 and beyond.
After serving 100+ enterprises, 93% of our clients were entangled with their legacy systems. Even when they wanted to make a switch, they couldn't move forward because of the risk of data loss during the migration phase.
This becomes the burden for most enterprises. But we're not just telling stories—the numbers speak for themselves: more than 1 billion transactions processed, and 1000+ traders onboarded. Within just 18 months, their automated energy trading platform achieved this.
That was just one example of how AI has become a major growth engine for their digital transformation journey.
If you're wondering how Artificial Intelligence can support you in your digital transformation journey, this complete guide is for you.
P.S - Looking for the digital transformation partner for your business?
What is AI in Digital Transformation?
In almost every industry, Artificial Intelligence is playing a great role in transforming business operations.
It’s no longer an add-on, but has become the necessity and integrating it into your business processes, operations, and products/services can bring incremental benefits such as -
Automation of repetitive tasks
Giving personalized recommendations to customers (which enhances their experience)
Making your employees more efficient, and much more
In media and entertainment industry, remember how streaming players such as Netflix and Spotify keep track of what you love watching?
It's all possible because of technology integrations, and AI has become the major driver of the digital transformation journey.
Take the case of the HR department. There are AI agents that can do CV screening, shortlist relevant profiles, and choose the ones suitable for a particular profile.
Let's say you're in the hospitality business and you want to increase your RevPAR this quarter. AI can help you achieve that goal.
As it can access guests' details at one place such as their preferences, booking history, and dietary restrictions, this helps you tailor your packages differently.
Not only will this enhance the guest experience, but you'll also be able to do more cross-sells and upsells.
What Are the Benefits of AI in Digital Transformation?
AI isn't just a technology, it's all about creating a mindset shift. Using Artificial Intelligence and Machine Learning can help you make responsible, data-driven decisions in the long run. Here's how AI can automate your work and augment your capabilities:
1. Enhancing Customer Experience Through Hyper-Personalization
AI-powered personalization transforms how brands interact with their customers. To sustain in the market and create a competitive edge, you need to provide personalized experiences to customers.
In 2025, if you're not using AI to analyze their behavioral patterns and identify their needs, then you won't be able to deliver individualized customer experiences.
AI is no longer optional; it has become a strategic imperative in 2025.
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This is what Prashant Jhakarwar, Founder of PixelPie Media, says.
Being in the marketing industry for many years, he knows that technology has become a major driver of smart marketing.
Today, advanced AI tools can do a lot of work for marketers and businesses, such as analyzing data, browsing customer behavior, purchase behavior, and real-time patterns.
This means that as buyer preferences change, you need to make your content and offers more fluid and adaptive so that your campaigns become more impactful and memorable.
Result? Such AI-driven personalization will boost your engagement rates and drive higher conversions.
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2. More Data-Driven Decisions
The amount of data that every business generates today is insane, and traditional data analysis methods can't keep up.
By integrating AI with data analytics, organizations can get a true picture of their business, operations, customers, and competitors. They can understand customer behavior, spot market trends, and make data-driven decisions.
In the healthcare sector, AI can help Radiologists to read medical images faster through machine learning algorithms to detect tumors and fractures in medical images.
This saves their time as they can focus more on speeding up diagnosis and less on analyzing huge amounts of medical data.
3. Automation of Workflows
When you integrate AI into your workflows, you're removing repetitive tasks and that massive shift in your digital strategy free up your employees to focus on strategic side of things.
Once you automate such workflows by bringing in intelligent tools, you focus on value realization and save time that would have been wasted on reinventing processes or restarting things from scratch.
Note: AI can't fix your broken workflows if your data is unclean. Of course, you will move faster in your business, but that comes at the cost of inefficiency.
4. Creating New Value Propositions
AI-driven digital transformation doesn't just help you on the cost side of things—it can grow your business and create more revenue streams through rapid prototyping, testing new products faster in the market, standardizing work processes, and creating great digital experiences for customers.
For instance, if you’re in ecommerce sector, you can still increase your revenue by running real-time offers on your digital channels based on how customers interact with your website or how their online behavior changes. That’s possible through the superpowers of AI.
AI Technologies Driving Digital Transformation for Businesses
1. Natural Language Processing
NLP has become part of everyday life, from prompting chatbots to using voice-operated GPS systems, Amazon's Alexa, and talking to Siri.
So, how do these systems analyze and understand human language? That's through natural language processing capabilities.
NLP is used in a variety of applications like ecommerce chatbots or those deployed in customer service departments that not only understand the intent of conversations but also respond to humans in a natural, conversational way.
Upside? NLP can be a good fit for tasks such as document translation, language translation, text-to-speech or speech-to-text, and summarization of long documents, articles, and news into shorter versions.
By using AI for digital transformation, businesses can unlock benefits such as enhanced customer service and improved internal processes.
You're running your hospitality business, and you want to measure guest feedback through surveys or feedback forms.
Manually doing so can take more time and effort, so the better way is to integrate AI into your processes, like doing sentiment analysis where AI will categorize the feedback by picking up positive and negative words. This way, you can see how and in what areas you can improve your guest service.
2. Computer Vision
As the name suggests, computer vision is an important tool that's making machines understand information from digital images or videos just like humans would do.
This technology is beneficial for performing tasks such as image detection, facial recognition, etc. In manufacturing, computer vision can be used for tasks from predictive maintenance to running production lines more smoothly.
Volkswagen, one of India's largest automotive players, wanted to become a global automotive player, but given its disconnected IT systems, it was not able to scale its IT systems.
After partnering with AWS, they created a digital production platform that acts as the central brain of their factories. Now Volkswagen uses computer vision as part of their digital strategy.
Their AI-powered systems can analyze thousands of car parts every hour and verify whether each component fits perfectly or not before it reaches customers.
Today, organizations are dealing with millions and trillions of data points, but doing such data analysis and predicting forecasts is another part of the story.
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Bret Tushaus, product management at software development company Deltek, explains that when it comes to making business decisions, every minute counts.
Predictive analytics can forecast the likelihood of project success, allocate resources efficiently, or identify which activities can be cost-effective in the long run. What used to take several days, weeks, or months can now be done in a few moments.
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This means that by leveraging predictive analytics in business operations, businesses can now predict consumer behavior, future trends, or potential risks.
That's how they can proactively adjust their strategies, get ahead of the curve, and create more business value.
4. Generative AI
Generative AI is a great tool for enterprise operations as it can increase productivity rates, slash content production timelines from weeks to days, and save huge costs for organizations.
The team at Microsoft started using generative AI tools to design and build their products.
Initially, designers used to create every single element for every screen or app, but now AI can learn to adapt how users interact with the screen to provide more personalized interactions.
Though their team members spend most of their time working with Figma, their designs are open-ended rather than fixed.
Victor Albahadly, a senior UX designer at Microsoft Studio Design Team, says earlier he needs to figure out what the user wants.
When building an application, he needs to see where users are coming from and what they want to do. But he has to do it not just for a single user but for all those who use the application.
But thanks to Generative AI, they no longer need to do this. It feels to them like now you're creating a book whose pages keep changing based on who's interacting with it.
5. Autonomous Systems
Autonomous systems in businesses can learn, respond, and act. They don't just wait for approval; rather, they can perform complex tasks with ease with little human intervention.
Microsoft launched Copilot agents to help its users perform a bunch of tasks from simple prompting to being fully autonomous. For example, customers can use it for sending emails and handling employee onboarding.
Microsoft describes these AI agents as the "apps of the AI world."
What Use Cases Do AI and Digital Transformation Create for Enterprises Across Industries in 2025?
If you're running a business, leading a team, or working in any industry (whether media, entertainment, or ecommerce), you need to embrace AI as it's no longer a buzzword anymore—it has become a key driver of business revolution.
The use of Artificial Intelligence and Machine Learning algorithms has become an enlightening force across all sectors such as healthcare, banking and financial services, logistics, retail, marketing, etc.
1. AI in Product Development
Artificial Intelligence has become the force multiplier for product managers as they can quickly test out prototypes, build products, and release them faster in the market.
Initially, it used to take multiple rounds of rework per iteration, delaying product launch time. Bad part? They end up creating a product that nobody wants or launching the product too late when customers' needs have been satisfied elsewhere.
Using AI as part of digital transformation is always a good move because you're compressing the time to market for your MVP, quickly receiving feedback from users, and then reiterating the product.
But that doesn’t mean it’s like adding fancy AI features to the product rather than understanding what customers actually need.
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Elaina O'Mahoney, CPO at Mural, shares her perspective on doing AI transformation in product development.
According to Elaina, "It's not just about using technology alone; it's about going back to the fundamentals of outcomes, customers, and metrics. If you overlook any of these three things, then you're going to build another feature list just for features' sake."
Whatever you're building—whether AI-related or not—understand what customers want, what problems you want to solve for them, and how you can better improve specific business outcomes.
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Note: Forget about just building ChatGPT integrations. Learn how you can create value for customers.
That's why it's important to understand that a successful digital transformation doesn't start with creating a product because your product managers and developers love creating it or you want to sell stuff to get money out there.
2. AI in Healthcare
Healthcare is evolving, and just like every industry is racing to harness AI in their processes, healthcare is no exception.
Best part? As machine learning algorithms can predict diseases in the early stages, doctors can diagnose them before they become a serious concern for patients.
Instead of new surgeons spending hours watching recorded videos, Johnson & Johnson has come up with AI-powered tools that can create reels from videos.
What used to take many days can now be learned within minutes, like how the new surgeons performed versus how others performed. Thus, watching hours of footage has been trimmed down to a few-second clips.
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According to Nicole Turner, senior director of global development at Johnson & Johnson, "Our goal here is to leverage the power of AI to bring clinical trials to more patients rather than patients coming to us."
You can move from being software-focused to something that's outcome-oriented. Today, banking has become more hyper-personalized because it's not about you creating a portal and pleasing your customers by selling your stuff.
It's about considering AI as your strategic partner where you're thinking and rethinking. This transformation is never easy, but the magic lies in how you integrate such technologies into your financial workflows.
That means the scope of AI is not just limited to data collection, but it can spot frauds faster.
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Raghav NyayaPati, who's leading AI projects at a top 10 AI bank, explains that in underwriting, banks receive thousands of loan applications and AI can quickly identify which applications are fraudulent or at high risk, and the filtered ones will go right to the human agent.
Overall, you need to use AI responsibly because if anything goes wrong, penalties will be high.
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4. AI in Ecommerce
The importance of digital transformation in ecommerce can't be ignored, and with personalization, the customer's journey is taken to the next level.
Every single customer that lands on your site and browses your page leaves data. When you collect such data at multiple touchpoints, you can either target them by running retargeting ads or show product recommendations that they love the most.
Either way, personalization is the driving force behind successful digital transformation, and AI can make that happen.
Even Amazon uses machine learning algorithms to keep track of shoppers' purchasing history, their past behavior, and preferences to suggest similar product items. This creates an engaging shopping experience for customers and improves your product sales.
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Nirav Sheth, Chairman of Annata (a Shopify Platinum partner), says integrating AI tools into ecommerce workflows can help you provide personalized experiences for customers, write product copy, and even help you with imagery creation.
That's how it automates everything while still keeping it tailored for your audience.
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The other area where Amazon uses Artificial Intelligence is dynamic pricing strategy. Its AI algorithms keep adjusting product prices in real-time based on multiple factors such as stock levels, competitor pricing, and supply and demand metrics.
Still, they're able to maintain their position as the lowest-price retailer for the last eight years.
Now, learning has become more hyper-personalized these days with the rise of adaptive learning platforms that adapt to the learner's capabilities and pace and teach them lessons in a way that makes learning more fun and engaging.
Similarly, the other benefits that AI-driven digital transformation provides in the education sector are that as administrative tasks such as grading and assignments can be automated, educators can now focus on teaching students.
6. AI in Transportation and Logistics
The role of AI and digital transformation can't be underrated in the logistics and transportation sector. One thing that remains unchanged is that technology was already in use for tracking trucks, rails, and ships through satellites.
But now big data and Artificial Intelligence have just made it simpler to use data to the fullest extent.
Today, AI is helping transportation and logistics firms in multiple ways, like deciding the best transportation route and predicting inventory demand. The use of robotics technology is another leap that makes inventory management in warehousing easy.
This means AI is now the answer to "do more stuff with less effort, less manpower, at lesser cost."
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Lutz Beck, CIO at Daimler Truck North America, shares his experience about how using technology such as AI helped him transform the entire logistics industry.
"People don't have emotions related to commercial vehicles as they do with passenger cars. But trucks have become the growth driver for the economy for transporting goods from one location to another."
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That's why his IT team is racing to make such technology transitions happen in the logistics industry. The company has now developed electric vehicles and added autonomous capabilities to make vehicles smarter.
Even in 2020, they developed a new ecommerce platform called "Excelerator" to help customers reach distribution providers so they can find the right vehicle parts quickly. This reduces vehicle downtime and enables quicker repairs.
9 Killer and Result-Driven Strategies to Take When Doing Digital Transformation Through AI
Here are a few ways you can transform your business digitally using AI:
1. Define Clear Vision and Strategy
The first step is to understand what you're doing to support the broader vision, whether for digital transformation or business transformation.
That's super important as it outlines the clear roadmap for you regarding people, process changes, and technology you want to deploy so you can achieve those high-level business objectives such as enhancing customer experience and generating more business revenue.
2. Decide Data Infrastructure First Before Building Advanced Applications
Don't expect technology alone will help you achieve your data transformation goals. You need to have clean, accessible, and high-quality data. Without that, your AI models will fail to deliver value.
3. Start with Pilot Projects Before Scaling
Before rolling out AI solutions on a wider level, you can start with pilot projects or proof of concept first to test how feasible the idea is and what results emerge after AI implementation in the project.
Pilot projects are a great way to test the highest-risk aspects before you commit more time and resources to them.
4. Use Agile Methodology
By pairing agile methodology with digital transformation, you become more responsive to technological changes and market dynamics.
Agile methodology is never a mandatory requirement, but if you want to adapt in the digital age, such an approach can make digital transformation faster.
Even the world's leading organizations, including Apple, Microsoft, and IBM, use an agile approach to deliver scalable products to the market. They can quickly test their ideas, become more responsive to market needs, and gain a competitive advantage.
5. Cross-Cultural Collaboration Is a Must
People are the engine behind successful AI-driven digital transformation initiatives. People and culture should always be at the top, and if cross-cultural collaboration isn't there, then no matter how well-designed your AI strategies are, they can't deliver business value.
6. Train Your Employees
Invest in employee training and hire candidates with expertise in AI, machine learning, and data science. Once you value employee growth, you can not only retain them for longer, but they will start delivering against rising expectations.
P.S – Don't have an expertise in building an AI powered software?
7. Choose the Right Tools and Technology Vendor
The digital transformation partner or external vendor you choose should have technical competencies, a business mindset, and a proven track record of delivering successful AI and digital transformation projects.
This means that the AI model that you use should produce the desired outcome, be free from bias, and systems should be secure, unbiased, and accurate.
9. Measure the Impact of AI Initiatives
It's time to measure the KPIs for your AI initiatives. For this, you need to analyze the results, take feedback, and iterate your AI solutions.
How Does the Future of AI Look in Digital Transformation?
The future of digital transformation with AI looks promising because it not only helps you automate your operations and enhance customer experience but also creates new business models that can drive significant revenue.
1. Multimodal AI
Multimodal AI models can produce different types of content such as text, images, audio, and video. What makes multimodal AI different from traditional AI models? These models can understand the world in a better way and act more like human beings.
They're multitask models. For example, you will ask the model through audio and the model will give you a text response. That's what multimodal capabilities can do.
Multimodal AI models can go beyond such data because they have insane capabilities, so they can ingest everything and work on different formats such as IoT data, log files, audio, etc.
2. Explainable AI (XAI)
As AI is pretty good at churning through huge amounts of data to solve everyday user problems, that's where explainable AI comes into the picture. Humans try to ask models about their performance, shortcomings, and what odd behaviors they can show.
Let's say your AI system disapproved a person's loan application. What will you say to your customer about why you disapproved it? AI will be able to tell you about the reasoning behind that process.
That's explainable AI.
How BigOhTech Can Help You with AI-Driven Digital Transformation Service?
At BigOhTech, our dedicated development team has expertise in AI, ML, and computer vision technology to help you achieve your business goals.
We've seen that businesses with $100,000 projects fail because their technology vendors focused on the technology side of things and don't understand their business model.
That's why we always take the human element at the heart of any transformation strategy.
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Having delivered a couple of projects in the past, Lufthansa is one example, and we helped them by modernizing their digital records management system.
Problem? Their existing DRM platform was built on an outdated tech stack, and given the huge amount of data to manage, this increased their cloud expenditure. The user interface was pretty bad, which made collaboration challenging between lessor and lessee.
We revamped their engineering system, which reduced their customer onboarding time from 4-5 months to 1 month.
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P.S. - Struggling with legacy tech stack?
FAQs:
Q1: How does AI and cloud power digital transformation for startups and enterprises?
AI and cloud computing go hand in hand. Just as cloud computing provides infrastructure and vast storage capabilities, this enables AI to process huge amounts of datasets.
From automation of complex processes in supply chain management to providing speedy customer support, AI and cloud computing can be used for predicting customer behavior, forecasting market demand, and personalization of services in real time.
Q2: What ROI can CEOs expect when integrating AI into their digital transformation roadmap?
Some organizations that implemented AI in their digital transformation projects experienced a 37% reduction in their total technology costs, while others noticed that such automation helped them launch their projects live in the market.
For every business, the goal and outcome are different like for some, it can be freeing up IT resources; for others, it can be about cost savings.
Q3: What industries benefit the most from AI-driven digital transformation?
These are some industries that largely benefit from AI-driven digital transformation:
Healthcare
Finance and banking
Product development
Transportation and logistics
Q4: Should enterprises build or buy AI solutions for digital transformation?
Enterprises should consider buying AI solutions when they’re not fully sure about long-term usage, when the technology is proprietary, or when they don’t have the internal team to build and maintain it. Buying is faster, cheaper upfront, and helps them see value much sooner.
However, building an AI solution makes sense when the company sees it as a long-term strategic bet. It takes more time and strong in-house expertise, but it gives complete control, the ability to customize deeply, and can even lead to better cost efficiency over the long run especially if AI becomes central to the business
Q5: How long does it take to see the results from AI driven digital transformation?
Most companies see results from AI-driven digital transformation in 3–6 months once the solution is deployed, fine-tuned and the team gets used to the new workflows.
The Total timeline depends heavily on whether you buy or build.
Buying an AI solution delivers faster results — sometimes almost instantly — if it solves the core problem and the team is trained.
Building takes longer due to development, testing, and integration, with full impact often taking 12–24 months for complex use cases.
Q6: How much does it cost to implement AI for digital transformation?
AI implementation can start as low as $10K–$50K for simple licensed tools and can increase to $200K–$1M+ for fully custom-built systems. The total cost of AI-driven digital transformation depends on several factors, including:
Use-case complexity (from basic automation to advanced custom AI models)
Data readiness (cleaning, labeling, migration, and integration)
Licensing model (fixed cost vs. pay-as-you-go token-based usage)
Whether you decide to buy, build, or use a hybrid AI model
Additional drivers such as ongoing maintenance, security and compliance needs, and external integrations (ERP, CRM, and other internal systems)
Q7: How do I choose the right development partner for my digital transformation journey?
Choosing the right technology partner will not be easy, but here are a few steps to help you get started -
The technology vendor should understand your business goals and what outcomes you need from a digital product.
Whether the digital transformation company has expertise in AI/ML technologies or not.
Check out their portfolio and skim through some of their case studies to see what projects they worked on in the past and what results they brought for them.
Do they have a customer-centric approach or not?
Check out their reviews and testimonials on their business listing websites such as Clutch, G2, Capterra, etc.
