Quality of faculty: that’s what compelled Matthew Belcher, an independent freelance web developer and student working towards a Bachelor in Computer Science, to enroll in the Open Institute of Technology (OPIT), allowing him to work with some of the top professionals in his chosen industry.

Matthew was recently elected program representative for the course, helping to guide the interests of over 100 students across the globe in discussions with the area chair and director to ensure that the course is fit for purpose and meets student needs.

Why OPIT?

In a recent interview, Matthew told us that the reason he chose OPIT to continue his education was the expertise of the faculty. He shared that he conducted intensive research into a variety of programs that would help him shape his interest and skill in technology into potential career opportunities.

Matthew felt that the OPIT faculty stood out as not just great teachers, but top-tier professionals with real-world experience in the kinds of industries he wants to work in. Their professional roles mean they offer an up-to-the-minute understanding of the changing market.

The Computer Science Program

The BSc in Computer Science is a fully accredited course delivered completely online over six 13-week terms.

The program delivers foundational skills, both theoretical and practical, in all aspects of computer science, including programming, software development, databases, cloud computing, cybersecurity, data science, and artificial intelligence. Students deliver a dissertation or project in the final term, and in term five, they can choose five electives from a pool of 27, or choose to specialize in one of five fields:

• Data Science and Artificial Intelligence
• Cloud Computing
• Cybersecurity
• Metaverse and Gaming
• Full Stack Development

The BSc in Computer Science is aimed at students interested in software development and engineering, data science, web development, app and game development, IT business analysis, cybersecurity, and database architecture.

Meet the Faculty

Now let’s meet some of the incredible faculty who influenced Matthew’s decision to select OPIT.

Art Sedighi

As well as teaching at OPIT, Art Sedighi is an adjunct professor at Johns Hopkins University and a professor at Purdue University Global. He was previously a partner at CDI Global, a senior cybersecurity solution architect at Amazon AWS, and head of high-performance computing and grid engineering at the Bank of America.

Sedighi has 20 years of experience planning, designing, developing, and having end-to-end ownership of cloud solutions. He has managed cross-functional teams and been responsible for driving adoption strategies across enterprises.

Sedighi teaches software engineering and cloud adoption in the BSc in Computer Science and is also a professor in the BSc in Digital Business program.

Lokesh Vij

As well as teaching in OPIT’s Computer Science Program, Lokesh is a database architect at Broadcom Inc., a semiconductor manufacturing firm in Canada, and a part-time professor at Seneca Polytechnic in Toronto.

Vij describes himself as a cloud and data evangelist, educator, and mentor. With over 20 years of rich experience, he has designed, developed, and delivered enterprise-scale data solutions across disparate source systems, data formats, and relational and non-relational databases.

His proven expertise includes enhancing business profitability by leveraging insights derived from diverse data sets, constructing decision support systems that convert transactional data into analytical formats. This, combined with data visualization techniques, allows him to articulate and clarify business insights effectively.

In the BSc in Computer Science program, he teaches cloud computing infrastructure, cloud development, cloud computing automation and ops, and cloud data stacks. He is also a professor of the BSc in Digital Business and the MSc in Applied Data Science & AI, also covering big data and cloud computing.

Tom Vazdar

Tom Vazdar is OPIT’s area chair for cybersecurity and also the CEO of Riskoria, which focuses on cybersecurity strategies. His areas of expertise include strategy services, AI and cybersecurity, AI infrastructure development, and compliance assurance and risk management.

Vazdar teaches computer security in both the BSc in Computer Science and the BSc in Digital Business programs, as well as for the MSc in Enterprise Cybersecurity.

Sylvester Kaczmarek

Sylvester Kaczmarek is a former Chief Science Officer at WeSpace Technologies and a former AI Mentor and Researcher at NASA. He is now an independent executive leading secure, safe, and resilient AI-driven space innovations, a science communicator, and an advisor to deep tech investors, governments, and startups.

In the past, he has specialized in the integration of artificial intelligence, robotics, cybersecurity, and edge computing in aerospace applications.

In OPIT’s BSc in Computer Science program, Kaczmarek teaches cartography and secure communications, secure software development, and parallel and distributed computing. He also teaches in the MSc in Enterprise Cybersecurity program.

Lorenzo Marvardi

As well as teaching at OPIT, Lorenzo Marvardi is a managing director at Accenture. With a background in cybersecurity management and security consulting, he has 15 years of experience as a security professional and executive, implementing security programs across different industries and geographies.

Marvardi teaches cybersecurity in both the BSc in Computer Science and the BSc in Digital Business programs.

Khaled Elbehiery

Khaled Elbehiery is a senior director and network engineer at Charter Communications. As well as teaching for OPIT, he is a part-time professor at Park University and DeVry University, both in the United States.

He describes himself as a professor, scientist, inventor, and author. He has publications on cloud engineering, quantum computing, space, robotics, bionics, microgravity, and modern educational methodologies.

Elbehiery teaches cloud and IoT security and computer networks on both the BSc in Computer Science and the MSc in Enterprise Cybersecurity programs.

Francesco Derchi

Francesco Derchi is a brand, innovation, and digital expert with over 14 years of experience. He is chair of digital business at OPIT, an advisory board member for Arsene Lippens, on the faculty at EHL in Switzerland and the Universita degli Studi di Genova, plus course director and contributor to the Harvard Business Review Italia.

Derchi teaches business strategy and digital marketing on both the BSc in Computer Science and the BSc in Digital Business, as well as on the MSc in Digital Business and Innovation.

In April 2025, the Open Institute of Technology (OPIT) invited Professor Andrea Gozzi, Head of Strategy at Partnership for the Digital Industries Ecosystem at Siemens, Italy, to talk about how new technologies are transforming industry.

Industry Is Driving Technological Innovation

According to Gozzi, who teaches in the OPIT BSc in Digital Business and MSc in Digital Business and Innovation programs, many of the young people he meets imagine that the development of technology like artificial intelligence (AI) and the Internet of Things (IoT) is being led by digital companies like Amazon and Apple. But, he adds, they haven’t really considered how industry is utilizing and leading in these fields.

Industry includes markets such as energy, aviation, and manufacturing. Gozzi explains how new technologies are transforming these industries and, in turn, how these industries are pioneering new technologies. As a result, industry represents a growing job market, especially for OPIT graduates.

Challenges to Industry

Gozzi started his discussion by explaining the modern challenges facing the industry today and how these challenges necessitate innovation. He identified three principal challenges:

• Geopolitical instability events like the war in Ukraine and changing tariffs are undermining supply lines, complicating contracts, and making sales unpredictable.
• Labor shortages are being caused by changing demographics and changing culture. Gozzi explained that in the past, people worked for one company for their entire lives, learning specialist skills and adding value throughout their working lives. Today, people tend to change jobs several times throughout their working lives, so to maximize their value, they need to be brought up to speed quicker, and companies need strategies to retain knowledge despite labor churn.
• Sustainability pressures are on the rise both in terms of meeting green regulations and ensuring that expensive factories provide a long-term return on investment.

To adapt to these challenges, industry is looking to develop innovative technological solutions.

Opportunities: AI, Digital Twins, Industrial IoT, and Robotics

Having set the scene, Gozzi dove into the types of technologies that industry is pioneering to adapt to challenge, and how they are pushing these technologies beyond their mainstream potential.

Artificial Intelligence (AI)

Gozzi explained how AI promises to be an industry game changer, especially in the quest to go from automated to adaptive manufacturing. Automated manufacturing can create products based on existing programming, recreating the same product perfectly every time while eliminating human error.

But the goal is to create machines that don’t just create one thing but can create anything, adapting as designs change. Adaptive manufacturing is one of the core goals of Industry 4.0, which is the next Industrial Revolution that is seeing automated, interconnected factories. Gozzi shared a compelling example of applications by Rolls-Royce for airplane engine production.

AI powers machines to handle more complex tasks independently, which requires them to be networked and connected. As a result, factories can collect data from every area and use it to optimize supply chains and resource allocation. This enables predictive maintenance, reducing downtime by around 50%, and scheduling activity, reducing yield losses by around 40%. Since factories represent major investments, maximizing productivity is essential to achieving a strong return on investment (ROI).

This same data is increasingly being used to iterate and test prototypes in the digital twin environment.

Digital Twins

According to Gozzi, today’s factories are created with intelligent interconnected machines that are adaptable and extendable and can provide strategic insights. The entire manufacturing system is connected by silent threads of information that can turn siloed data into a much larger picture.

These threads form the neural network of digital twins, which are virtual replicas of physical systems that can be used to monitor and optimize operations, simulate actions before execution, and accelerate innovation. New production techniques and designs can be tested virtually before being tested in the real world, allowing processes to be optimized for quality and efficiency. Here, Gozzi shared a compelling example from Siemens’ accelerator ecosystem which creates replicas of factories in the metaverse.

IIoT and Robotics

In the factories themselves, manufacturers rely on advanced robotics connected by the Industrial Internet of Things (IIoT) to carry out tasks independently. IIoT ensures that a centralized intelligence integrates every element of production in real-time. This not only allows robots to do their jobs but also ensures that issues can be identified and solutions executed through the digital twin. The digital twin can also be used to teach robots new tasks tested and piloted virtually in the digital twin.

Meanwhile, robots must be mobile, AI-driven, and integrated into the factory’s ecosystem. It is AI that has enabled robots to become aware of their environment, enabling new behaviors such as picking pieces from a non-uniform set and placing them where they are required. This may seem small, but it is something that robots have never been able to do and represents one of the biggest recent breakthroughs in manufacturing.

AI is also enabling robots to safely work alongside human workers in manufacturing settings. These collaborative robots, called “cobots,” are another recent development that promises to be transformative.

Cybersecurity

Gozzi explained that all this requires advanced connectivity and a closed network with a “zero trust” architecture to mitigate security threats. Hackers, viruses, and other network failures don’t just represent the potential loss of valuable and confidential data, but also a major safety risk if cobots are interfered with and begin to act unsafely.

Powerful and secure industrial closed networks are being enabled by 5G, but these networks still need to be monitored by cybersecurity continuously in real-time.

The Future of Industry

Industry is modernizing quickly, and technology is playing an increasingly important role. This is manifesting in the development of smart adaptive factories using a mix of AI, advanced robotics, and digital twins. Industrial IoT, strong connected networks, and advanced cybersecurity support this. The demand for talent that understands these technologies and their applications will only increase in the coming years.

Moreover, Gozzi reassures students that there is no question that technology will replace real people in some positions. Humans will still be needed to collaborate and work side by side with robots. This will require people to learn new skills, in particular, a data-driven mindset and approach to problem-solving.

Both OPIT’s BSc in Digital Business and MSc in Digital Business and Innovation are designed to prepare students for these kinds of careers.

Source:

• Agenda Digitale, published on May 16th, 2025

By Riccardo Ocleppo, Founder and Director of OPIT – Open Institute of Technology

AI ethics requires ongoing commitment. Organizations must integrate guidelines and a corporate culture geared towards responsibility and inclusiveness, preventing negative consequences for individuals and society.

In the world of artificial intelligence, concerns about algorithmic bias are coming to the forefront, calling for a collective effort to promote ethical practices in the development and use of AI.

This implies the need to understand the multiple causes and potential consequences of the biases themselves, identify concrete solutions and recognize the key role of academic institutions in this process.

Bias in AI is a form of injustice, often systemic, that can be embedded in algorithms. Its origins are many, but the main culprit is almost always the data set used to train the models. If this data reflects inequalities or prejudices present in society, the risk is that AI will absorb and reproduce them, consolidating these distortions.

But bias can also manifest itself in the opposite direction. This is what happened some time ago with Google Gemini. The generative AI system developed by Google, in an attempt to ensure greater inclusivity, ended up generating content and images completely disconnected from the reality it was supposed to represent.

Further complicating the picture is the very nature of AI models, which are often characterized by complex algorithms and opaque decision-making processes. This complexity makes it difficult to identify, and therefore correct, biases inherent in the systems.

Ethical Data Management to Reduce Bias in AI

Adopting good data management practices is essential to address these issues. The first step is to ensure that the datasets used for training are diverse and representative. This means actively seeking data that includes a wide variety of demographic, cultural, and social contexts, so as to avoid AI exclusively reproducing existing and potentially biased models.

Alongside data diversification, it is equally important to test models on different demographic groups. Only in this way can latent biases that would otherwise remain invisible be highlighted. Furthermore, promoting transparency in algorithms and decision-making processes is crucial. Transparency allows for critical control and makes all actors involved in the design and use of AI accountable.

Strategies for ethical and responsible artificial intelligence

Building ethical AI is not an isolated action, but an ongoing journey that requires constant attention and updating. This commitment is divided into several fundamental steps. First, ethical guidelines must be defined. Organizations must clearly establish the ethical standards to follow in the development and use of AI, inspired by fundamental values ​​such as fairness, responsibility and transparency. These principles serve as a compass to guide all projects.

It is also essential to include a plurality of perspectives in the development of AI. Multidisciplinary teams, composed of technologists, ethicists, sociologists and representatives of the potentially involved communities, can help prevent and correct biases thanks to the variety of approaches. Last but not least, promote an ethical culture : in addition to establishing rules and composing diverse teams, it is essential to cultivate a corporate culture that places ethics at the center of every project. Only by integrating these values ​​​​in the DNA of the organization can we ensure that ethics is a founding element of the development of AI.

The consequences of biased artificial intelligence

Ignoring the problem of bias can have serious and unpredictable consequences, with profound impacts on different areas of our lives. From the reinforcement of social inequalities to the loss of trust in AI-based systems, the risk is to fuel skepticism and resistance towards technological innovation. AI, if distorted, can negatively influence crucial decisions in sectors such as healthcare, employment and justice. Think, for example, of loan selection algorithms that unfairly penalize certain categories, or facial recognition software that incorrectly identifies people, with possible legal consequences. These are just some of the situations in which an unethical use of AI can worsen existing inequalities.

University training and research to counter bias in AI

Universities and higher education institutions have a crucial responsibility to address bias and promote ethical practices in AI development. Ethics must certainly be integrated into educational curricula. By including ethics modules in AI and computer science courses, universities can provide new generations of developers with the tools to recognize and address bias, contributing to more equitable and inclusive design. Universities can also be protagonists through research.

Academic institutions, with their autonomy and expertise, can explore the complexities of bias in depth, developing innovative solutions for detecting and mitigating bias. Since the topic of bias is multidimensional in nature, a collaborative approach is needed, thus fostering interdisciplinary collaboration. Universities can create spaces where computer scientists, ethicists, lawyers, and social scientists work together, offering more comprehensive and innovative solutions.

But that’s not all. As places of critical thinking and debate, universities can foster dialogue between developers, policy makers, and citizens through events, workshops, and conferences. This engagement is essential to raise awareness and promote responsible use of AI.

In this direction, several universities have already activated degree courses in artificial intelligence that combine advanced technical skills (in areas such as machine learning, computer vision and natural language processing) with training that is attentive to ethical and human implications.

Academic Opportunities for an Equitable AI Future

More and more universities around the world – including Yale and Oxford – are also creating research departments dedicated to AI and ethics.

The path to ethical AI is complex, but it also represents an opportunity to build a future where technology truly serves the common good.

By recognizing the root causes of bias , adopting responsible data practices, and engaging in ongoing and vigilant development, we can reduce the unintended effects of biased algorithms. In this process, academic institutions – thanks to their expertise and authority – are at the forefront, helping to shape a more equitable and inclusive digital age.

• Agenda Digitale

Source:

• TechFinancials, published on May 16th, 2025

By Zorina Alliata

• TechFinancials

Source:

• Wired, published on May 01st, 2025

People are using ChatGPT’s new image generator to take part in viral social media trends. But using it also puts your privacy at risk—unless you take a few simple steps to protect yourself.

By Kate O’Flaherty

• Wired

Source:

• LADBible and Yahoo News, published on May 01st, 2025

You’ve probably seen them all over Instagram

By James Moorhouse

• LADBible and Yahoo News

It’s not uncommon to hear stories from people who have committed several years to obtaining a university degree, only to discover it doesn’t fit the purposes they need when entering the business world.

Why? Even though universities spend years developing their degree courses in areas such as economics, business, and biomedical science, it is challenging to keep up with the latest technological advancements due to the lengthy approval process and a lack of experts on staff.

Today, artificial intelligence (AI), big data, cloud computing, and cybersecurity are beginning to impact every aspect of our business lives, regardless of whether you work in a cutting-edge science lab or an antiquities museum. However, many graduates fail to leverage this new technology and adapt it to their careers.

This is why OPIT – the Open Institute of Technology – was born, to offer affordable and accessible courses that bridge the gap between what is taught in traditional universities and what the job market requires.

How Is the Job Market Changing?

According to the World Economic Forum’s Future of Jobs Report 2025, 92 million jobs will be displaced by new technologies, though 170 million new jobs will be created that utilize new technology.

The report suggests that 39% of the key skills required in the job market will change by 2030. These include hard technical skills and the soft skills needed to work in creative environments where change is a constant.

New job descriptions will look for big data specialists, fintech engineers, and AI and machine learning specialists. Additionally, employers will also be seeking creative thinkers who are flexible and agile, as well as resilient in the face of change.

Technology-focused jobs that are in increasing demand include:

• Machine Learning Engineer – Developing and refining algorithms that enable systems to learn from data and improve performance.
• Natural Language Processing Specialist – Developing chatbots that can understand users, communicate naturally, and provide valuable assistance.
• AI Ethicist – Ensuring that AI is developed and deployed with broader social, legal, and moral implications considered.
• Data Architect – Gathering raw data from different sources and designing infrastructure that consolidates this information and makes it usable.
• Chief Data Officer – Leading a company’s data collection and application strategy, ensuring data-driven decision-makers.
• Cybersecurity Engineer – Building information security systems and IT architecture, and protecting them from unauthorized access and cyberattacks.

Over the next few years, we can expect most jobs to require an understanding of the applications for cutting-edge technology, if not how to manage the technical backend. Leaders need to know how to implement AI and automation to save time and reduce errors. Researchers need to understand how to leverage data to reveal new findings, and everyone needs to understand how to work in secure digital environments.

The conclusion is that in tomorrow’s job market, workers will need to find the right balance of technical and human skills to thrive.

A New Approach to Learning Is Needed

Learning requires a fundamental change. Just as businesses need to be adaptable, places of higher learning need to be more adaptable too, keeping their offerings up-to-date and reducing the timescales required to accredit and deliver new courses fit for the current job market.

This aligns with OPIT’s mission to unlock progress and employment on a global scale by providing high-quality and affordable education in the field of technology.

How Does OPIT Work?

OPIT is accredited with the MFHEA (Malta Further and Higher Education Authority) in accordance with the European Qualifications Framework (EQF).

Working with an evolving faculty of experts, OPIT offers a technological education aligned with the current and future career market.

Currently, OPIT offers two Bachelor’s degrees:

• Digital Business – Focuses on merging business acumen with digital fluency, bridging the strategy-execution gap in the evolving digital age.
• Modern Computer Science – Establishes 360-degree foundation skills, both theoretical and applicative, in all aspects of today’s computer science. It includes programming, software development, the cloud, cybersecurity, data science, and AI.

OPIT also offers four Master’s degrees:

• Digital Business & Innovation – Empowers professionals to drive innovation by leveraging digital technologies and AI, covering topics such as strategy, digital marketing, customer value management, and AI applications.
• Responsible Artificial Intelligence – Combines technical expertise with a focus on the ethical implications of modern AI, including sustainability and environmental impact.
• Enterprise Cybersecurity – Integrates technical and managerial expertise, equipping students with the skills to implement security solutions and lead cybersecurity initiatives.
• Applied Data Science & AI – Focuses on the intersection between management and tech with no computer science prerequisites. It provides foundation applicative courses coupled with real-world business problems approached with data science and AI.

Courses offer flexible online learning, with both live online-native classes and recorded catch-up sessions. Every course is hands-on and career-aligned, preparing students for multiple career options while working with top professionals.

Current faculty members include Zorina Alliata, principal AI strategist at Amazon; Sylvester Kaczmarek, AI mentor and researcher at NASA; Andrea Gozzi, head of Strategy and Partnership for the Digital Industries Ecosystem at Siemens; and Raj Dasgupta, AI and machine learning scientist at the U.S. Naval Research Laboratory.

OPIT designs its courses to be accessible and affordable, with a dedicated career services department that offers one-on-one career coaching and advice.

Graduating From OPIT

OPIT recently held its first graduation ceremony for students in 2025. Students described their experience with OPIT as unique, innovative, and inspiring. Share the experience of OPIT’s very first graduates in the video here.

If you are curious to learn more about the OPIT student community, OPIT can connect you with a current student. Just reach out.

The world is rapidly changing. New technologies such as artificial intelligence (AI) are transforming our lives and work, redefining the definition of “essential office skills.”

So what essential skills do today’s workers need to thrive in a business world undergoing a major digital transformation? It’s a question that Alan Lerner, director at Toptal and lecturer at the Open Institute of Technology (OPIT), addressed in his recent online masterclass.

In a broad overview of the new office landscape, Lerner shares the essential skills leaders need to manage – including artificial intelligence – to keep abreast of trends.

Here are eight essential capabilities business leaders in the AI era need, according to Lerner, which he also detailed in OPIT’s recent Master’s in Digital Business and Innovation webinar.

An Adapting Professional Environment

Lerner started his discussion by quoting naturalist Charles Darwin.

“It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is the most adaptable to change.”

The quote serves to highlight the level of change that we are currently seeing in the professional world, said Lerner.

According to the World Economic Forum’s The Future of Jobs Report 2025, over the next five years 22% of the labor market will be affected by structural change – including job creation and destruction – and much of that change will be enabled by new technologies such as AI and robotics. They expect the displacement of 92 million existing jobs and the creation of 170 million new jobs by 2030.

While there will be significant growth in frontline jobs – such as delivery drivers, construction workers, and care workers – the fastest-growing jobs will be tech-related roles, including big data specialists, FinTech engineers, and AI and machine learning specialists, while the greatest decline will be in clerical and secretarial roles. The report also predicts that most workers can anticipate that 39% of their existing skill set will be transformed or outdated in five years.

Lerner also highlighted key findings in the Accenture Life Trends 2025 Report, which explores behaviors and attitudes related to business, technology, and social shifts. The report noted five key trends:

• Cost of Hesitation – People are becoming more wary of the information they receive online.
• The Parent Trap – Parents and governments are increasingly concerned with helping the younger generation shape a safe relationship with digital technology.
• Impatience Economy – People are looking for quick solutions over traditional methods to achieve their health and financial goals.
• The Dignity of Work – Employees desire to feel inspired, to be entrusted with agency, and to achieve a work-life balance.
• Social Rewilding – People seek to disconnect and focus on satisfying activities and meaningful interactions.

These are consumer and employee demands representing opportunities for change in the modern business landscape.

Key Capabilities for the AI Era

Businesses are using a variety of strategies to adapt, though not always strategically. According to McClean & Company’s HR Trends Report 2025, 42% of respondents said they are currently implementing AI solutions, but only 7% have a documented AI implementation strategy.

This approach reflects the newness of the technology, with many still unsure of the best way to leverage AI, but also feeling the pressure to adopt and adapt, experiment, and fail forward.

So, what skills do leaders need to lead in an environment with both transformation and uncertainty? Lerner highlighted eight essential capabilities, independent of technology.

Capability 1: Manage Complexity

Leaders need to be able to solve problems and make decisions under fast-changing conditions. This requires:

• Being able to look at and understand organizations as complex social-technical systems
• Keeping a continuous eye on change and adopting an “outside-in” vision of their organization
• Moving fast and fixing things faster
• Embracing digital literacy and technological capabilities

Capability 2: Leverage Networks

Leaders need to develop networks systematically to achieve organizational goals because it is no longer possible to work within silos. Leaders should:

• Use networks to gain insights into complex problems
• Create networks to enhance influence
• Treat networks as mutually rewarding relationships
• Develop a robust profile that can be adapted for different networks

Capability 3: Think and Act “Global”

Leaders should benchmark using global best practices but adapt them to local challenges and the needs of their organization. This requires:

• Identifying what great companies are achieving and seeking data to understand underlying patterns
• Developing perspectives to craft global strategies that incorporate regional and local tactics
• Learning how to navigate culturally complex and nuanced business solutions

Capability 4: Inspire Engagement

Leaders must foster a culture that creates meaningful connections between employees and organizational values. This means:

• Understanding individual values and needs
• Shaping projects and assignments to meet different values and needs
• Fostering an inclusive work environment with plenty of psychological safety
• Developing meaningful conversations and both providing and receiving feedback
• Sharing advice and asking for help when needed

Capability 5: Communicate Strategically

Leaders should develop crisp, clear messaging adaptable to various audiences and focus on active listening. Achieving this involves:

• Creating their communication style and finding their unique voice
• Developing storytelling skills
• Utilizing a data-centric and fact-based approach to communication
• Continual practice and asking for feedback

Capability 6: Foster Innovation

Leaders should collaborate with experts to build a reliable innovation process and a creative environment where new ideas thrive. Essential steps include:

• Developing or enhancing structures that best support innovation
• Documenting and refreshing innovation systems, processes, and practices
• Encouraging people to discover new ways of working
• Aiming to think outside the box and develop a growth mindset
• Trying to be as “tech-savvy” as possible

Capability 7: Cultivate Learning Agility

Leaders should always seek out and learn new things and not be afraid to ask questions. This involves:

• Adopting a lifelong learning mindset
• Seeking opportunities to discover new approaches and skills
• Enhancing problem-solving skills
• Reviewing both successful and unsuccessful case studies

Capability 8: Develop Personal Adaptability

Leaders should be focused on being effective when facing uncertainty and adapting to change with vigor. Therefore, leaders should:

• Be flexible about their approach to facing challenging situations
• Build resilience by effectively managing stress, time, and energy
• Recognize when past approaches do not work in current situations
• Learn from and capitalize on mistakes

Curiosity and Adaptability

With the eight key capabilities in mind, Lerner suggests that curiosity and adaptability are the key skills that everyone needs to thrive in the current environment.

He also advocates for lifelong learning and teaches several key courses at OPIT which can lead to a Bachelor’s Degree in Digital Business.