Before the COVID-19 pandemic, most businesses viewed digitalization as only an additional avenue for marketing their products or services. In the post-pandemic world though, digitalization has become the very lifeblood of survival for these businesses.
But implementing an efficient digital business strategy is no easy task. After all, a digital transformation calls for fundamentally reshaping how a business operates.
However, one look at what technology can do for you and your business is enough to make you understand that the complex digital transformation process is well worth it. If all of this is new to you, don’t worry. You can master all the necessary digital skills to reap the benefits of digitalization by completing the Open Institute of Technology’s Bachelor’s Degree in Digital Business. Alternatively, you can further your skills with the Institute’s Master’s Degree in Applied Digital Business.
Without further ado, let’s discuss eight genuine benefits of embracing digitalization and implementing digital business strategies.
1. Data-Driven Decision-Making
Efficiency. Innovation. Sustainable success. These desirable outcomes can only be reached with data-driven decision-making. While traditional decision-making mostly relies on experience, modern data-driven decision-making leverages the power of artificial intelligence (AI) to analyze vast amounts of data swiftly and accurately.
Of course, artificial intelligence brings much more to the corporate world beyond data analysis. This innovative technology can automate administrative tasks, provide instant customer responses, and enhance overall operational agility. All of these make managerial and business decisions and processes significantly faster.
That’s precisely why OPIT’s study programs feature courses dedicated to artificial intelligence in the business setting, from a general introduction to AI principles in the digital economy. The goal of these courses is simple – help you understand why, how, and when to use AI in business decision-making and beyond.
But as powerful as AI is, you can’t solely rely on technology in your decision-making process. AI is only there to help you make this process more comprehensive and strategized. This technology will also help you spend less time on mundane, control-based tasks, allowing you to focus on your judgment, critical thinking, and problem-solving.
Luckily, all of these skills are also covered by various Digital Business courses at OPIT, allowing you to become the best digital-era manager and decision-maker you can be.
2. Faster Time to Market
All the invaluable data gathered by artificial intelligence and other digital tools can also do wonders in the research and development department. With so much data at hand, businesses should have no trouble improving their existing products or services or launching new ones.
The latter process is especially important as the time it takes for a product to go from conceptualization to market availability can be rather lengthy. But what used to take months or years can now be done in weeks, days, or even hours, all thanks to digitalization.
Businesses can rely on modern technologies to rapidly test, pilot, iterate, and launch new products and services, significantly enhancing their agility in the ever-evolving business world. And hey, if a product or a service doesn’t quite work, you’ll be able to tell this almost immediately through online feedback and product reviews.
Using these valuable insights, businesses can revise their offerings to suit their customers’ preferences, needs, and interests. The result? Nothing but product excellence and customer satisfaction.
3. New Sales Channels
Dominating the business world is all about finding new ways to reach, engage, and retain customers. The good news? The digital-age business world offers seemingly endless opportunities to do this. You just need to know where to look.
Granted, your job doesn’t stop when a new channel is identified. Rather, it transforms. Now, it’s up to you to know how to use that channel effectively. To do so, you’ll need to learn about digital business models, as virtually every sales channel has a dedicated one.
Arguably, the most important thing to cover is how digital business models differ from traditional models (especially if you’ve only ever worked with the latter). And that’s precisely what OPIT’s “Digital Business Models” module covers.
You’ll learn just how vital online platforms, e-commerce, and digital marketing are in shaping modern business strategies. Use this knowledge to successfully tap into new markets and connect with a broader audience.
Naturally, there’s one online channel that’ll play critical role here – social media. Luckily for business owners and managers, most customers are active on at least one social media platform, essentially making the global population a prospect for sales.
4. Increased Market Share
For most businesses, the ultimate goal is to boost revenue, improve bargaining power, and strengthen competitive position. First step? Capturing a more substantial portion of the market. Fortunately, doing so is much easier now that most of the global population is within reach through digital business strategies.
So, it’s no wonder digital transformation has become essential to growing a brand. This process facilitates everything you need to establish a robust market presence – better financial performance, media activity, and advertising capabilities.
Best of all? You can use digital business strategies to only boost your market share or completely dominate your industry. It’s all up to you and how you harness the power of digitalization.
That’s why OPIT’s Applied Digital Business program contains a course titled “Maximizing Impact in the Digital Economy.” From gradual scaling to growth hacking, this course equips you with the insights and skills needed to ensure sustained success in virtually any industry.
5. Better Customer Interaction
Reaching and retaining new customers are equally important. But how can you do this? By ensuring most (if not all) of their interactions with the business are positive, of course. Naturally, digital transformation can help in this regard as well.
After all, the digital environment offers countless possibilities for improving the customer relationship with a brand. From streamlined online transactions to personalized communication through various digital channels, there’s virtually no area of the customer experience that digital transformation can’t positively impact. With this process, it’s all about simplicity, real-time services, and tailored experiences. And there’s hardly a customer that doesn’t love these things.
Granted, many (digital) elements are involved in achieving this desirable outcome, including artificial intelligence, automation, and digital marketing. But don’t worry; the OPIT’s programs extensively cover each element.
Take digital marketing as an example. Whether you’re interested in gaining an understanding of the key concepts of this dynamic field or delving into advanced strategies, there’s a module tailored to your needs.
6. Real-Time Transactions
As previously mentioned, customers love real-time services. In the past, this was hardly possible, as businesses were limited by time and infrastructure constraints. But not anymore. With digital tools, the 24/7 concept becomes a reality.
Customers can look at business offerings and make a purchase at any time of the day or night, breaking free from the traditional constraints of operating hours. All they need is a few clicks, and voilà – their transaction is complete.
This is made possible by innovative technologies like Blockchain, which dramatically enhances transaction speed while minimizing costs and any chances of fraud. Of course, this also means that this technology is covered by OPIT’s undergraduate program, which looks into the Blockchain’s transformative impact on business practices.
7. Easy Talent Acquisition
So far, this article has focused on how digital business strategies can benefit a brand’s relationship with customers. But these strategies can also revolutionize the process of talent acquisition. Of course, this is equally important, as there’s no successful business without a talented and capable workforce.
Before, recruiting top talent was often a challenging and time-consuming endeavor. Now, attracting talent (and the right talent for your business at that) is almost effortless. How?
Well, digital tools have got your back every step of the way. From job-matching sites like LinkedIn attracting candidates based on their professional profiles to automated systems streamlining the hiring process, digital tools have completely transformed talent acquisition.
That’s not to mention the endless opportunities working from home has opened up both for businesses and employees. Thanks to digitalization, the whole world is basically your talent pool.
8. Higher Revenue
Though each of the mentioned benefits is essential for business success in and of itself, they also have a cumulative impact on one of the most crucial business metrics: revenue. Investing in digitalization might seem like a major undertaking, but this impact makes every penny worth it.
Let’s recap what you can get with effective digital business strategies. You can get more effective systems and productive employees, better decision-making and judgment, improved products and sales channels, and a long-lasting (and interactive) relationship with customers. All of these create a robust foundation for revenue growth.
Reap the Full Benefits of Digital Business Strategies
There’s no doubt about it – effective digital business strategies can transform the trajectory of virtually any business. But for these strategies to work, they must be carried out with precision, knowledge, and strategic foresight.
That’s where OPIT’s Bachelor’s Degree in Digital Business and Master’s Degree in Applied Digital Business come into play.
Regardless of the digital business career you’re interested in (e.g., digital business consultant, digital marketing specialist, or digital transformation specialist), these courses will equip you with the necessary skills to stay ahead in a globally connected world.
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From the same author
Read the articleSource:
- Agenda Digitale, published on November 25th, 2025
In recent years, the word ” sustainability ” has become a firm fixture in the corporate lexicon. However, simply “doing no harm” is no longer enough: the climate crisis , social inequalities , and the erosion of natural resources require a change of pace. This is where the net-positive paradigm comes in , a model that isn’t content to simply reduce negative impacts, but aims to generate more social and environmental value than is consumed.
This isn’t about philanthropy, nor is it about reputational makeovers: net-positive is a strategic approach that intertwines economics, technology, and corporate culture. Within this framework, digitalization becomes an essential lever, capable of enabling regenerative models through circular platforms and exponential technologies.
Blockchain, AI, and IoT: The Technological Triad of Regeneration
Blockchain, Artificial Intelligence, and the Internet of Things represent the technological triad that makes this paradigm shift possible. Each addresses a critical point in regeneration.
Blockchain guarantees the traceability of material flows and product life cycles, allowing a regenerated dress or a bottle collected at sea to tell their story in a transparent and verifiable way.
Artificial Intelligence optimizes recovery and redistribution chains, predicting supply and demand, reducing waste and improving the efficiency of circular processes .
Finally, IoT enables real-time monitoring, from sensors installed at recycling plants to sharing mobility platforms, returning granular data for quick, informed decisions.
These integrated technologies allow us to move beyond linear vision and enable systems in which value is continuously regenerated.
New business models: from product-as-a-service to incentive tokens
Digital regeneration is n’t limited to the technological dimension; it’s redefining business models. More and more companies are adopting product-as-a-service approaches , transforming goods into services: from technical clothing rentals to pay-per-use for industrial machinery. This approach reduces resource consumption and encourages modular design, designed for reuse.
At the same time, circular marketplaces create ecosystems where materials, components, and products find new life. No longer waste, but input for other production processes. The logic of scarcity is overturned in an economy of regenerated abundance.
To complete the picture, incentive tokens — digital tools that reward virtuous behavior, from collecting plastic from the sea to reusing used clothing — activate global communities and catalyze private capital for regeneration.
Measuring Impact: Integrated Metrics for Net-Positiveness
One of the main obstacles to the widespread adoption of net-positive models is the difficulty of measuring their impact. Traditional profit-focused accounting systems are not enough. They need to be combined with integrated metrics that combine ESG and ROI, such as impact-weighted accounting or innovative indicators like lifetime carbon savings.
In this way, companies can validate the scalability of their models and attract investors who are increasingly attentive to financial returns that go hand in hand with social and environmental returns.
Case studies: RePlanet Energy, RIFO, and Ogyre
Concrete examples demonstrate how the combination of circular platforms and exponential technologies can generate real value. RePlanet Energy has defined its Massive Transformative Purpose as “Enabling Regeneration” and is now providing sustainable energy to Nigerian schools and hospitals, thanks in part to transparent blockchain-based supply chains and the active contribution of employees. RIFO, a Tuscan circular fashion brand, regenerates textile waste into new clothing, supporting local artisans and promoting workplace inclusion, with transparency in the production process as a distinctive feature and driver of loyalty. Ogyre incentivizes fishermen to collect plastic during their fishing trips; the recovered material is digitally tracked and transformed into new products, while the global community participates through tokens and environmental compensation programs.
These cases demonstrate how regeneration and profitability are not contradictory, but can actually feed off each other, strengthening the competitiveness of businesses.
From Net Zero to Net Positive: The Role of Massive Transformative Purpose
The crucial point lies in the distinction between sustainability and regeneration. The former aims for net zero, that is, reducing the impact until it is completely neutralized. The latter goes further, aiming for a net positive, capable of giving back more than it consumes.
This shift in perspective requires a strong Massive Transformative Purpose: an inspiring and shared goal that guides strategic choices, preventing technology from becoming a sterile end. Without this level of intentionality, even the most advanced tools risk turning into gadgets with no impact.
Regenerating business also means regenerating skills to train a new generation of professionals capable not only of using technologies but also of directing them towards regenerative business models. From this perspective, training becomes the first step in a transformation that is simultaneously cultural, economic, and social.
The Regenerative Future: Technology, Skills, and Shared Value
Digital regeneration is not an abstract concept, but a concrete practice already being tested by companies in Europe and around the world. It’s an opportunity for businesses to redefine their role, moving from mere economic operators to drivers of net-positive value for society and the environment.
The combination of blockchain, AI, and IoT with circular product-as-a-service models, marketplaces, and incentive tokens can enable scalable and sustainable regenerative ecosystems. The future of business isn’t just measured in terms of margins, but in the ability to leave the world better than we found it.
Read the articleSource:
- Raconteur, published on November 06th, 2025
Many firms have conducted successful Artificial Intelligence (AI) pilot projects, but scaling them across departments and workflows remains a challenge. Inference costs, data silos, talent gaps and poor alignment with business strategy are just some of the issues that leave organisations trapped in pilot purgatory. This inability to scale successful experiments means AI’s potential for improving enterprise efficiency, decision-making and innovation isn’t fully realised. So what’s the solution?
Although it’s not a magic bullet, an AI operating model is really the foundation for scaling pilot projects up to enterprise-wide deployments. Essentially it’s a structured framework that defines how the organisation develops, deploys and governs AI. By bringing together infrastructure, data, people, and governance in a flexible and secure way, it ensures that AI delivers value at scale while remaining ethical and compliant.
“A successful AI proof-of-concept is like building a single race car that can go fast,” says Professor Yu Xiong, chair of business analytics at the UK-based Surrey Business School. “An efficient AI technology operations model, however, is the entire system – the processes, tools, and team structures – for continuously manufacturing, maintaining, and safely operating an entire fleet of cars.”
But while the importance of this framework is clear, how should enterprises establish and embed it?
“It begins with a clear strategy that defines objectives, desired outcomes, and measurable success criteria, such as model performance, bias detection, and regulatory compliance metrics,” says Professor Azadeh Haratiannezhadi, co-founder of generative AI company Taktify and professor of generative AI in cybersecurity at OPIT – the Open Institute of Technology.
Platforms, tools and MLOps pipelines that enable models to be deployed, monitored and scaled in a safe and efficient way are also essential in practical terms.
“Tools and infrastructure must also be selected with transparency, cost, and governance in mind,” says Efrain Ruh, continental chief technology officer for Europe at Digitate. “Crucially, organisations need to continuously monitor the evolving AI landscape and adapt their models to new capabilities and market offerings.”
An open approach
The most effective AI operating models are also founded on openness, interoperability and modularity. Open source platforms and tools provide greater control over data, deployment environments and costs, for example. These characteristics can help enterprises to avoid vendor lock-in, successfully align AI to business culture and values, and embed it safely into cross-department workflows.
“Modularity and platformisation…avoids building isolated ‘silos’ for each project,” explains professor Xiong. “Instead, it provides a shared, reusable ‘AI platform’ that integrates toolchains for data preparation, model training, deployment, monitoring, and retraining. This drastically improves efficiency and reduces the cost of redundant work.”
A strong data strategy is equally vital for ensuring high-quality performance and reducing bias. Ideally, the AI operating model should be cloud and LLM agnostic too.
“This allows organisations to coordinate and orchestrate AI agents from various sources, whether that’s internal or 3rd party,” says Babak Hodjat, global chief technology officer of AI at Cognizant. “The interoperability also means businesses can adopt an agile iterative process for AI projects that is guided by measuring efficiency, productivity, and quality gains, while guaranteeing trust and safety are built into all elements of design and implementation.”
A robust AI operating model should feature clear objectives for compliance, security and data privacy, as well as accountability structures. Richard Corbridge, chief information officer of Segro, advises organisations to: “Start small with well-scoped pilots that solve real pain points, then bake in repeatable patterns, data contracts, test harnesses, explainability checks and rollback plans, so learning can be scaled without multiplying risk. If you don’t codify how models are approved, deployed, monitored and retired, you won’t get past pilot purgatory.”
Of course, technology alone can’t drive successful AI adoption at scale: the right skills and culture are also essential for embedding AI across the enterprise.
“Multidisciplinary teams that combine technical expertise in AI, security, and governance with deep business knowledge create a foundation for sustainable adoption,” says Professor Haratiannezhadi. “Ongoing training ensures staff acquire advanced AI skills while understanding associated risks and responsibilities.”
Ultimately, an AI operating model is the playbook that enables an enterprise to use AI responsibly and effectively at scale. By drawing together governance, technological infrastructure, cultural change and open collaboration, it supports the shift from isolated experiments to the kind of sustainable AI capability that can drive competitive advantage.
In other words, it’s the foundation for turning ambition into reality, and finally escaping pilot purgatory for good.
-
Go to all authors
Related posts
Source:
- Agenda Digitale, published on November 25th, 2025
In recent years, the word ” sustainability ” has become a firm fixture in the corporate lexicon. However, simply “doing no harm” is no longer enough: the climate crisis , social inequalities , and the erosion of natural resources require a change of pace. This is where the net-positive paradigm comes in , a model that isn’t content to simply reduce negative impacts, but aims to generate more social and environmental value than is consumed.
This isn’t about philanthropy, nor is it about reputational makeovers: net-positive is a strategic approach that intertwines economics, technology, and corporate culture. Within this framework, digitalization becomes an essential lever, capable of enabling regenerative models through circular platforms and exponential technologies.
Blockchain, AI, and IoT: The Technological Triad of Regeneration
Blockchain, Artificial Intelligence, and the Internet of Things represent the technological triad that makes this paradigm shift possible. Each addresses a critical point in regeneration.
Blockchain guarantees the traceability of material flows and product life cycles, allowing a regenerated dress or a bottle collected at sea to tell their story in a transparent and verifiable way.
Artificial Intelligence optimizes recovery and redistribution chains, predicting supply and demand, reducing waste and improving the efficiency of circular processes .
Finally, IoT enables real-time monitoring, from sensors installed at recycling plants to sharing mobility platforms, returning granular data for quick, informed decisions.
These integrated technologies allow us to move beyond linear vision and enable systems in which value is continuously regenerated.
New business models: from product-as-a-service to incentive tokens
Digital regeneration is n’t limited to the technological dimension; it’s redefining business models. More and more companies are adopting product-as-a-service approaches , transforming goods into services: from technical clothing rentals to pay-per-use for industrial machinery. This approach reduces resource consumption and encourages modular design, designed for reuse.
At the same time, circular marketplaces create ecosystems where materials, components, and products find new life. No longer waste, but input for other production processes. The logic of scarcity is overturned in an economy of regenerated abundance.
To complete the picture, incentive tokens — digital tools that reward virtuous behavior, from collecting plastic from the sea to reusing used clothing — activate global communities and catalyze private capital for regeneration.
Measuring Impact: Integrated Metrics for Net-Positiveness
One of the main obstacles to the widespread adoption of net-positive models is the difficulty of measuring their impact. Traditional profit-focused accounting systems are not enough. They need to be combined with integrated metrics that combine ESG and ROI, such as impact-weighted accounting or innovative indicators like lifetime carbon savings.
In this way, companies can validate the scalability of their models and attract investors who are increasingly attentive to financial returns that go hand in hand with social and environmental returns.
Case studies: RePlanet Energy, RIFO, and Ogyre
Concrete examples demonstrate how the combination of circular platforms and exponential technologies can generate real value. RePlanet Energy has defined its Massive Transformative Purpose as “Enabling Regeneration” and is now providing sustainable energy to Nigerian schools and hospitals, thanks in part to transparent blockchain-based supply chains and the active contribution of employees. RIFO, a Tuscan circular fashion brand, regenerates textile waste into new clothing, supporting local artisans and promoting workplace inclusion, with transparency in the production process as a distinctive feature and driver of loyalty. Ogyre incentivizes fishermen to collect plastic during their fishing trips; the recovered material is digitally tracked and transformed into new products, while the global community participates through tokens and environmental compensation programs.
These cases demonstrate how regeneration and profitability are not contradictory, but can actually feed off each other, strengthening the competitiveness of businesses.
From Net Zero to Net Positive: The Role of Massive Transformative Purpose
The crucial point lies in the distinction between sustainability and regeneration. The former aims for net zero, that is, reducing the impact until it is completely neutralized. The latter goes further, aiming for a net positive, capable of giving back more than it consumes.
This shift in perspective requires a strong Massive Transformative Purpose: an inspiring and shared goal that guides strategic choices, preventing technology from becoming a sterile end. Without this level of intentionality, even the most advanced tools risk turning into gadgets with no impact.
Regenerating business also means regenerating skills to train a new generation of professionals capable not only of using technologies but also of directing them towards regenerative business models. From this perspective, training becomes the first step in a transformation that is simultaneously cultural, economic, and social.
The Regenerative Future: Technology, Skills, and Shared Value
Digital regeneration is not an abstract concept, but a concrete practice already being tested by companies in Europe and around the world. It’s an opportunity for businesses to redefine their role, moving from mere economic operators to drivers of net-positive value for society and the environment.
The combination of blockchain, AI, and IoT with circular product-as-a-service models, marketplaces, and incentive tokens can enable scalable and sustainable regenerative ecosystems. The future of business isn’t just measured in terms of margins, but in the ability to leave the world better than we found it.
Source:
- Raconteur, published on November 06th, 2025
Many firms have conducted successful Artificial Intelligence (AI) pilot projects, but scaling them across departments and workflows remains a challenge. Inference costs, data silos, talent gaps and poor alignment with business strategy are just some of the issues that leave organisations trapped in pilot purgatory. This inability to scale successful experiments means AI’s potential for improving enterprise efficiency, decision-making and innovation isn’t fully realised. So what’s the solution?
Although it’s not a magic bullet, an AI operating model is really the foundation for scaling pilot projects up to enterprise-wide deployments. Essentially it’s a structured framework that defines how the organisation develops, deploys and governs AI. By bringing together infrastructure, data, people, and governance in a flexible and secure way, it ensures that AI delivers value at scale while remaining ethical and compliant.
“A successful AI proof-of-concept is like building a single race car that can go fast,” says Professor Yu Xiong, chair of business analytics at the UK-based Surrey Business School. “An efficient AI technology operations model, however, is the entire system – the processes, tools, and team structures – for continuously manufacturing, maintaining, and safely operating an entire fleet of cars.”
But while the importance of this framework is clear, how should enterprises establish and embed it?
“It begins with a clear strategy that defines objectives, desired outcomes, and measurable success criteria, such as model performance, bias detection, and regulatory compliance metrics,” says Professor Azadeh Haratiannezhadi, co-founder of generative AI company Taktify and professor of generative AI in cybersecurity at OPIT – the Open Institute of Technology.
Platforms, tools and MLOps pipelines that enable models to be deployed, monitored and scaled in a safe and efficient way are also essential in practical terms.
“Tools and infrastructure must also be selected with transparency, cost, and governance in mind,” says Efrain Ruh, continental chief technology officer for Europe at Digitate. “Crucially, organisations need to continuously monitor the evolving AI landscape and adapt their models to new capabilities and market offerings.”
An open approach
The most effective AI operating models are also founded on openness, interoperability and modularity. Open source platforms and tools provide greater control over data, deployment environments and costs, for example. These characteristics can help enterprises to avoid vendor lock-in, successfully align AI to business culture and values, and embed it safely into cross-department workflows.
“Modularity and platformisation…avoids building isolated ‘silos’ for each project,” explains professor Xiong. “Instead, it provides a shared, reusable ‘AI platform’ that integrates toolchains for data preparation, model training, deployment, monitoring, and retraining. This drastically improves efficiency and reduces the cost of redundant work.”
A strong data strategy is equally vital for ensuring high-quality performance and reducing bias. Ideally, the AI operating model should be cloud and LLM agnostic too.
“This allows organisations to coordinate and orchestrate AI agents from various sources, whether that’s internal or 3rd party,” says Babak Hodjat, global chief technology officer of AI at Cognizant. “The interoperability also means businesses can adopt an agile iterative process for AI projects that is guided by measuring efficiency, productivity, and quality gains, while guaranteeing trust and safety are built into all elements of design and implementation.”
A robust AI operating model should feature clear objectives for compliance, security and data privacy, as well as accountability structures. Richard Corbridge, chief information officer of Segro, advises organisations to: “Start small with well-scoped pilots that solve real pain points, then bake in repeatable patterns, data contracts, test harnesses, explainability checks and rollback plans, so learning can be scaled without multiplying risk. If you don’t codify how models are approved, deployed, monitored and retired, you won’t get past pilot purgatory.”
Of course, technology alone can’t drive successful AI adoption at scale: the right skills and culture are also essential for embedding AI across the enterprise.
“Multidisciplinary teams that combine technical expertise in AI, security, and governance with deep business knowledge create a foundation for sustainable adoption,” says Professor Haratiannezhadi. “Ongoing training ensures staff acquire advanced AI skills while understanding associated risks and responsibilities.”
Ultimately, an AI operating model is the playbook that enables an enterprise to use AI responsibly and effectively at scale. By drawing together governance, technological infrastructure, cultural change and open collaboration, it supports the shift from isolated experiments to the kind of sustainable AI capability that can drive competitive advantage.
In other words, it’s the foundation for turning ambition into reality, and finally escaping pilot purgatory for good.
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