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Since generative AI exploded onto the scene with the release of ChatGPT (still less than two years ago, unbelievably), we’ve seen that it has the potential to impact many jobs.

Perhaps one that will most obviously be affected is customer support. After all, chatbots are a flagship use case for generative AI, and the process of transitioning from human agents to automated systems began long before the emergence of language models (LLMs).

Does this mean everyone working in the field should be looking for new jobs, as the days of humans staffing customer support lines and helpdesks are numbered?

I don’t think so. A report by Harvard Business Review found that of 13 essential tasks involved in customer support and customer service, just four of them could be fully automated, while five could be augmented by AI to help humans work more effectively.

So, let’s explore the ways in which I believe the day-to-day work of customer support agents will be disrupted. I’ll also take a look at how professionals in the field can adapt to ensure they stay relevant in the AI-powered business landscape of the near future.

The Role Of Generative AI In Customer Support

Perhaps one of the most obvious applications – and certainly one we’re seeing enthusiastic adoption of – is chatbots. In the past, most of us will probably have experienced the frustration of dealing with slow, clumsy and far-from-intelligent voice recognition and automated customer support technology. Today, thanks to the application of chatbots built on LLMs, bots can have conversations that are close to being as dynamic and flexible as those of humans.

This means that we will increasingly see them used to deal with routine inquiries. However, they will also become capable of providing personalized and instant responses across many more in-depth and edge-case customer support situations. This will free human agents up to spend time on cases that require a human touch. This might be those needing case-specific knowledge not found in data the AI can access, multi-faceted problems or those that require input and collaboration from different departments.

Generative AI can also be used to build and maintain support knowledge bases. They can be continuously kept up-to-date with the latest developments in best practices so that human agents will always have access to the most current information and insights.

It’s also great at sentiment analytics. In a support context, this means it can quickly analyze large volumes of tickets or inquiries, categorizing them according to the sentiment of the customer. This could even take place in real-time, for example, by guiding human agents on how to respond during person-to-person interactions.

Generative AI can also be used to draft automated but personalized responses to email inquiries, making sure that messages carry a consistent tone while providing customers with advice relevant to their specific issues.

As we move forward, we can also expect to see even more advanced applications.

Predictive customer support will focus on solving customer issues before they are even raised. This could involve automating warnings, messages or prompts to install updates based on alerts from other AI agents working elsewhere in the business. For example, if a number of users are having difficulty accessing a service, then other users who are likely to want to use the service could be warned beforehand, enabling them to make alternative arrangements. Ultimately, this will reduce the chance of losing customers due to poor support experiences.

How Can Customer Support Professionals Stay Relevant?

I don’t believe that we will immediately see mass human redundancy across customer support roles. After all, people will always be required to cope with unexpected and unique challenges that always occur. I do, however, believe that professionals in the field who prepare themselves for the AI revolution will increase their chances of remaining useful and valued.

While AI will take some jobs, new jobs will emerge. There will be opportunities for customer support professionals who want to transition into new positions, such as AI trainers, who improve the quality of automated responses, and AI-human collaboration specialists, who will manage the integration of AI into human workforces.

This will involve staying up-to-date with the latest developments in workplace trends and AI technology, as well as adopting a habit of continuous learning and upskilling.

More value will also be placed on those who show themselves to be adept at human, soft skills that machines don’t yet have a good understanding of. These include emotional intelligence, empathy, and complex problem-solving – all core skills in customer support.

On the flip side, showing that you are capable of collaborating with AI and using it to augment your ability to carry out routine everyday tasks more quickly and efficiently will also make you valuable.

Overall, I believe that the secret to success is to learn to treat AI as both a tool and as a partner. Rather than attempting to compete with it in order to stay relevant, learn how and when it can be used to boost your own efficiency and productivity. And focus on developing human skills that AI can’t replicate when it comes to solving customer problems and improving customer experience.

credit: Bernard Marr

As artificial intelligence continues to reshape industries, understanding which jobs remain secure is crucial. While AI’s impact on the job market is undeniable, not all roles are equally vulnerable. Most jobs will be augmented to some extent, but those involving complex human emotions, advanced decision-making, and creative thinking are generally safer from complete automation. Here are some of the most AI-resistant careers:

Skilled Tradespeople

Skilled tradespeople, such as electricians and carpenters, possess hands-on expertise and problem-solving skills that AI cannot replicate. These roles require working in varied environments, adapting to unique challenges, and applying practical knowledge in real-time. The physical dexterity, spatial awareness, and on-the-spot decision-making needed in these trades make them resilient to automation. While AI can assist with tools and planning, the nuanced skills of a tradesperson remain irreplaceable.

Healthcare Professionals

Healthcare professionals, including doctors, nurses, and therapists, are essential roles that AI can only partially augment. AI can assist in diagnostics, patient monitoring, and even robotic surgeries. Still, the core of healthcare revolves around human empathy, interpersonal skills, and ethical judgment—qualities that AI cannot replicate. Understanding patient needs, providing compassionate care, and making critical ethical decisions ensure that healthcare professionals remain indispensable.

Strategic Decision-Makers

Executives and entrepreneurs occupy roles requiring high-level strategic decision-making and leadership capabilities. These roles involve understanding complex, multifaceted problems, weighing risks and benefits, and making decisions that steer organizations toward success. While AI can provide data-driven insights and assist in analysis, the nuanced understanding of business dynamics, stakeholder interests, and long-term vision are uniquely human attributes safeguarding these jobs from automation.

Creative Professions

Creative professionals, such as artists, writers, and designers, bring originality and a personal touch to their work that AI struggles to match. Generative AI tools can perform simple creative tasks and even assist in the creative process, but the essence of creativity involves inspiration, cultural subtleties, and deep emotional connections. The ability to convey human experiences, emotions, and unique perspectives ensures that creative professionals remain at the forefront of their fields, with AI serving as a supportive tool rather than a replacement.

Emergency Responders

Emergency responders, including firefighters, paramedics, and police officers, perform roles demanding quick thinking, human judgment, and physical presence. These jobs require the ability to assess unpredictable situations, make life-saving decisions, and provide immediate assistance. The complex and dynamic nature of emergencies is beyond the capabilities of current AI technologies. The physical and emotional demands placed on emergency responders highlight the irreplaceable value of human skills in these critical roles.

Embracing Uniquely Human Skills

The roles mentioned above emphasize human interaction, emotional intelligence, and creativity—qualities that AI can’t replicate yet. As AI continues to evolve, it’s essential to focus on developing and enhancing these uniquely human skills to stay ahead. By leveraging our innate abilities in empathy, strategic thinking, and creativity, we can ensure a harmonious coexistence with AI and secure our place in the future job market.

While AI will continue to augment and transform various aspects of work, the importance of human expertise, intuition, and emotional intelligence remains paramount. Embracing change, continuously learning, and adapting to new technologies will be key to thriving in an AI-enhanced world. By understanding the roles that are most resistant to automation, we can better prepare ourselves and future generations for a dynamic and ever-evolving job market.

So, what job is most safe from AI? It’s the ones that require the irreplaceable touch of human skills—those that make us uniquely human.

credit: Bernard Marr

Shadow AI, the unsanctioned use of AI tools in the workplace, is becoming a significant concern for businesses. This article explores the risks and opportunities of this trend, offering practical strategies for harnessing employee innovation while maintaining security and compliance.

In the ever-evolving landscape of business technology, a new phenomenon is emerging from the shadows: Shadow AI. Much like its predecessor, shadow IT, this trend is characterized by employees using unauthorized AI tools to boost their productivity and streamline their workflows. While this may sound alarming at first, it’s actually a sign of an innovative and forward-thinking workforce. The challenge for businesses lies in harnessing this creative energy without compromising security or compliance.

The Shadow AI Dilemma

Picture this: Tom, a marketing executive, discovers ChatGPT and starts using it to draft compelling email campaigns. Meanwhile, Sarah in finance is leveraging an AI-powered analytics tool to gain deeper insights into company spending patterns. Both are seeing impressive results, but neither tool has been vetted or approved by the IT department.

This scenario is playing out in companies across the globe. A recent study by Salesforce found that 49% of people have used generative AI, with over one-third using it daily. In the workplace, this translates to a significant number of employees bringing AI tools into their daily tasks without official sanction.

The Risks Of Unchecked AI Use

While the initiative shown by employees like Sarah and Tom is commendable, unchecked AI use can pose serious risks:

1. Data Security: When employees input company data into public AI tools, they may inadvertently expose sensitive information. Samsung learned this lesson the hard way in 2023 when they had to ban ChatGPT after staff entered confidential data.
2. Compliance Issues: AI tools that haven’t been vetted may not meet industry-specific compliance requirements, potentially leading to regulatory violations.
3. Inconsistent Output: Different AI tools can produce varying results, potentially undermining the uniformity of products, services, or customer experiences.
4. Ethical Concerns: Unchecked AI use in areas like HR could lead to biased decision-making, opening the company up to discrimination claims.

Turning Challenge Into Opportunity

Despite these risks, Shadow AI presents a unique opportunity for businesses to tap into their employees’ innovative spirit. Here’s how companies can navigate this new terrain:

1. Acknowledge and Embrace Innovation

Instead of shutting down unsanctioned AI use, recognize it as a sign that your team is actively seeking ways to work smarter. This innovative drive is a valuable asset in today’s competitive landscape.

2. Develop Clear AI Policies

Create comprehensive guidelines that outline which AI tools are approved for use, what kind of data can be input, and how to use these tools responsibly. Communicate these policies clearly and frequently to ensure all employees are on the same page.

3. Provide Training and Resources

Offer workshops, webinars, and e-learning modules to educate employees on the safe and effective use of AI tools. This not only mitigates risks but also empowers your workforce to leverage AI to its full potential.

4. Encourage Open Communication

Foster an environment where employees feel comfortable discussing their AI needs and discoveries. This open dialogue can help IT departments stay ahead of the curve and identify valuable tools that could be officially adopted.

5. Invest in Secure AI Solutions

Consider developing or investing in AI tools that meet your specific business needs and security requirements. This proactive approach can provide employees with powerful, vetted alternatives to public AI tools.

6. Regular Security Audits

Implement regular security checks to identify any unsanctioned AI use and address potential vulnerabilities before they become serious issues.

The Future Of AI In The Workplace

As AI continues to evolve and integrate into our daily work lives, the line between sanctioned and unsanctioned use will likely blur. Forward-thinking companies will need to stay agile, continuously updating their AI policies and practices to keep pace with technological advancements.

Harnessing The Power Of AI Safely

Shadow AI doesn’t have to be a threat. By acknowledging employee innovation, implementing clear policies, providing education, and fostering open communication, businesses can turn this challenge into a competitive advantage. The goal is not to stifle creativity but to channel it through secure, compliant pathways.

In this new era of AI-enhanced workplaces, the most successful companies will be those that find the sweet spot between innovation and security. They’ll empower their employees to leverage AI tools while maintaining robust safeguards against potential risks.

As we navigate this exciting frontier, remember: the shadow of AI doesn’t have to be ominous. With the right approach, it can illuminate new paths to productivity, creativity, and success in your organization.

credit: Bernard Marr

AI is going to change healthcare forever. In the near future, we can look forward to revolutionary new cures and treatments, personalized medicine, and a new generation of hospitals and facilities where super-smart robots take care of everything from cleaning to brain surgery.

At least – so we’re told. Now, I’m a believer in the power of AI to change the world for the better. But I can also plainly see that there’s a lot of hype around it. Technology companies stand to make trillions from selling it, and they all want us to believe their models and algorithms are the ones that will change the world.

In a world that’s quickly becoming flooded with AI washing, it’s critical that we learn how to cut through the hype and marketing bluster. So here I’ll take a look at how well one of the most frequent claims – that it will transform the fields of healthcare, medicine and wellbeing – stands up to scrutiny.

Where Are We Today?

So far, attempts to improve research and delivery of healthcare using AI have provided some encouraging success stories, as well as some clear examples of over-exaggerated expectations.

In drug and vaccine discovery, for example, it accelerated the discovery of mRNA vaccines for COVID-19. The same technology is now being used to create new protections against many other diseases. And generative AI built on similar technology to ChatGPT has also been used to create new immunotherapy drugs.

It has been used to analyze and interpret medical scans, images, medical records and tissue samples, and has been shown to be able to spot signs of diseases such as cancer and Alzheimer’s disease.

According to the American College Of Surgeons, “Most research shows that scan interpretation from AI is more robust and accurate than those from radiologists, often picking up small, rare spots in the images.”

It can shorten the length of time we need to stay in hospital, with one study of patients diagnosed with pulmonary embolism finding that those triaged with AI tools were able to return home an average of two days earlier.

The use of chatbots to answer patient questions or assist with the training of clinical staff, as well as analytics tools to help hospitals plan their use of resources more efficiently, all promise to streamline delivery and ultimately improve outcomes.

However, that isn’t to say that there haven’t also been missteps and over-inflated claims, particularly in the early days. In 2017, a partnership between IBM and MD Anderson Cancer Center was discontinued after it was found that the Watson Health system’s decision-making wasn’t accurate enough, creating a “credibility gap” with physicians.

In 2002, a study of online symptom-checker and self-diagnosis tools, some of which involve using AI to provide self-triage, found that “overall, the diagnostic and triage accuracy of symptom checkers are variable and of low accuracy … this study demonstrates that reliance upon symptom checkers could pose significant patient safety hazards.”

It should also be noted that despite the fact that many hospitals and healthcare providers are exploring the use of AI systems for creating efficiencies in administerial, record-keeping and staffing processes, it’s hard to find evidence that this has yet led to significant cost savings or improvements in patient care.

What Are The Experts Saying?

If we look beyond the words of marketers and the CEOs of big tech companies, opinions vary on the value that AI has – or will – bring to the field of healthcare.

Geneticist and cardiologist Dr Eric Topol, author of Deep Medicine, says that while AI will probably never replace a thorough physical examination by an experienced doctor, many applications are already proving highly valuable. These include self-administered kits that test for urinary tract infections and analyze lung problems from the sound of a cough.

In the future, he believes, mobile phones are likely to provide inexpensive ultrasound scans, and recognize early warning signs of diabetes from a picture of the retina.

Perhaps most valuable of all, he suggests, will be the ability of AI to restore the “human element” to medicine. By handling routine tasks, AI will free up doctors to spend more face-to-face time with patients, enabling them to develop a better understanding of their condition.

This is a position echoed by Dr Fei-Fei Li, director of Stanford University’s Institute for Human-Centered AI, who says “We’re seeing the medical profession using AI technology … [doctors] tell me that medical summaries are very painful … they take away from patients. Now you can get a language model to help.”

However an article in MIT Technology review presents a more cautionary outlook. Tools designed to diagnose disease or predict outbreaks could be trained on limited or biased data – for example, research has shown that some tools are less effective with female patients simply because less women take part in medical studies.

And Dr. Robert Glatter, assistant professor of emergency medicine at the Zucker School of Medicine, together with Dr. Peter Papadakos, professor of anesthesiology and surgery at the University of Rochester Medical Center, in their article No AI Can Ever Learn The Art Of Medicine, argue “Even with the advent and ongoing evolution of AI … empathy is best learned and communicated in the form of bedside teaching by humans – not AI or chatbots.”

The Verdict – Hype Or Reality?

While AI has undoubtedly already made significant impacts and seems likely to become more valuable as we move forward, it’s unlikely to be the literal panacea that will cure all of our ills.

However, we’re in the very early days of the AI revolution, and successes in fields such as drug discovery and detection of early warning signals clearly demonstrate that the potential to improve care and outcomes is real.

Challenges – particularly around data privacy, implementation costs and training of healthcare professionals in its use – will need to be overcome before the most optimistic predictions become viable.

As in other fields, professionals agree that its most valuable applications will involve augmenting rather than replacing human skills, experience and expertise.

For the technology companies building tools, keeping this firmly in mind while developing the next generation of AI-enhanced medical applications will be key to driving real change that will benefit us all.

Credit: Bernard Marr

he AI revolution is well underway, and I believe just about any business or organization can benefit by automating routine tasks, augmenting decision-making and optimizing operations and processes.

However, AI can also harm a business if it isn’t used cautiously. So, it’s very surprising to me that many companies and organizations don’t have any form of official AI policy in place.

Among the most serious risks are breaching privacy and confidentiality, exposing sensitive data, and inadvertently infringing copyright.

Creating such a policy should be at the top of just about every organization’s to-do list, regardless of size or industry. So, in this article, I’ll explore the risks that companies are exposing themselves to by allowing unregulated AI use, as well as the benefits of a well-thought-out policy when it comes to navigating the complex and sometimes dangerous waters of business AI.

Why Is Using AI Dangerous?

Long gone are the days when only large companies like Google or Microsoft were using AI. On a daily basis, millions of businesses are leveraging technology such as chatbots for customer support, generative content creation and audience analytics in marketing, screening job applicants in HR, detecting fraudulent transactions, optimizing supply chain operations or extracting business intelligence insights from their data.

Unfortunately, in my experience, many of them are unaware of the risks they’re leaving themselves open to.

Data privacy and security concerns are perhaps the most obvious, but still overlooked on a surprisingly frequent basis. Employees using tools like ChatGPT to create summaries or respond to emails are often unaware that they’re potentially exposing confidential information to the world.

Even if they are, some simply assume it isn’t a problem due to the fact they haven’t been told not to do it!

Several companies have already fallen foul of risks associated with a lack of regulation around AI.

For example, in 2023, Samsung banned the use of ChatGPT after finding that staff had entered sensitive data.

Another example is that HR departments routinely use AI tools to screen job applicants. However, unless proper care is taken to mitigate the risk of bias, this could lead to discrimination, potentially leaving the business open to legal action.

The same goes for businesses that are using AI tools that make decisions that can affect people’s lives – for example, processing loan applications or allocating healthcare resources.

When it comes to IP and copyright issues, businesses relying on AI-generated content could inadvertently find themselves using content without permission. Several court cases are currently being brought by artists and news agencies, saying their work was used to train algorithms without their permission. The outcome is uncertain right now, but could potentially lead to trouble further down the road for businesses using these tools.

And accountability is also an important issue. Are businesses and employees fully aware of their need to take responsibility for decisions that AI makes on their behalf? A lack of transparency and explainability inherent to many AI systems may make it difficult for them to do so. But this is unlikely to work as an excuse if they should find themselves in hot water due to their actions!

Getting any of this wrong could cause huge financial, legal and reputational damage to a company. So what can be done?

How An AI Policy Mitigates Risk

If a business wants to take advantage of the transformative opportunities offered by AI, a clear, detailed and comprehensive AI policy is essential.

Establishing guidelines around what constitutes acceptable and unacceptable use of AI should be the first step in safeguarding against its potential risks. However, it’s crucial to understand that an effective AI policy goes beyond mere risk mitigation – it’s also a powerful enabler for innovation and growth.

A well-crafted AI policy doesn’t just defend; it empowers. By clearly outlining how AI should be used to enhance productivity and drive innovation, it provides a framework within which employees can confidently explore and leverage AI technologies. This clarity fosters an environment where creative solutions are nurtured within safe and ethical boundaries.

Addressing these issues proactively will also help businesses identify the technological elements necessary for the safe and responsible use of AI.

For example, understanding the data policies around public cloud-based AI tools such as ChatGPT allows businesses to recognize where more private, secure systems — such as on-premises infrastructure – could be essential.

With this policy in place, any organization positions itself on far firmer ground. Rather than stifling them, it will empower organizations with the knowledge that they can experiment and innovate with confidence. An AI policy acts as a launchpad, setting up a framework for responsible and effective AI use that can drive competitive advantage.

The rapid adoption of AI across industries and the risks that this has created means an AI policy isn’t just a good idea — it’s critical to future-proofing any business.

Additionally, putting an acceptable AI use policy in place helps a company to position itself as a serious player in the AI game, rather than just another business jumping on the bandwagon. In an era where AI capabilities are rapidly becoming a benchmark for industry leadership, having a clear AI policy positions your company as a responsible, forward-thinking player. This can be incredibly attractive to investors, partners, and top talent who prioritize ethical standards and corporate responsibility.

It also helps to demonstrate to customers, investors and other stakeholders that an organization is committed to building trust and implementing AI in a transparent and ethical way.

This will be invaluable when it comes to hiring and retaining talent. People with the skills and experience needed to implement organizational AI systems are highly sought-after. Naturally, they’re attracted to companies that are able to demonstrate that they are serious and mature in their outlook and practices when it comes to AI.

This is something that I believe all leaders need to prioritize if they want to benefit from the opportunities offered by AI. A comprehensive AI policy doesn’t only defend; it also enables. It clarifies for all employees how AI should be used to enhance productivity and innovation, fostering an environment where creative solutions are nurtured within safe and ethical boundaries.

credit: Bernard Marr

Two years ago most people hadn’t heard of generative AI, but now it’s everywhere. Shortly after its release, ChatGPT became the fastest growing app in history. Jump forward to today and Apple has just announced plans to build it into its iPhones and it’s hard to find a piece of software that doesn’t offer generative capabilities.

However, there’s undoubtedly a lot of hype, confusion, and even fear around it. This ranges from enthusiastic advocates announcing that it’s going to solve all of the world’s problems to doom-mongers predicting that it will make millions of us redundant or even spell the end of human creativity.

So, here’s my overview of what I see as the biggest misconceptions about this revolutionary but misunderstood technology. Personally, I believe that most people can find a way to use it to help them in their work or day-to-day lives, but first, they need to understand it. Hopefully, this is helpful for cutting through the hype and getting to the facts.

Generative AI Is Intelligent

Let’s start with the biggie. Generative AI, like ChatGPT, mimics certain qualities of natural intelligence, specifically the ability to process, interpret, and create language.

However, natural (human or animal) intelligence has many facets, like reasoning, abstract thought, emotional intelligence, intuition, memory, creativity, and communication.

While generative AI excels in communication and memory, it only touches on those other aspects.

When ChatGPT or another large language model (LLM) creates output, it follows probability rules derived that it learns during its training. This means its “thought processes” are far more limited and less sophisticated than ours.

Is this real intelligence? No, it’s called “artificial” intelligence for a reason. It can do amazing things, but it’s still just an algorithm – albeit a very complex one!

Generative AI Will Replace Human Creativity

If computers can write stories and draw pictures, does that mean we don’t need human authors and artists anymore? The simple answer is no. Generative AI doesn’t fulfill all the criteria for true intelligence or creativity.

It doesn’t really have new ideas in the same way that humans do. Its creativity is only informed by data rather than by feelings, emotions, original thoughts and personal experience of the world.

A common reaction of humans to AI-generated content is that it’s bland and lacking in humanity. At first glance, this may not seem like a very scientific analysis, but when you consider it in the context of the limitations of generative AI, it makes sense.

Human creatives have nothing to fear from generative AI. While it can produce a formulaic novel or a generic picture quickly, it’s far from creating art that inspires and makes us think.

Generative AI Only Creates Words And Pictures

Ask most people what generative AI is, and they will probably tell you about ChatGPT and how it generates words or Dall-E 2 and how it can create pictures. While these are the most well-known use cases, they are just the tip of the iceberg of what AI can do today.

Generative AI tools are also available to create music, voice, and even video.

But it doesn’t stop there. Did you know it has also been used to create new medicines – including a new immunotherapy treatment for cancer?

It also creates data – known as synthetic data – which can be used to train AI algorithms and carry out statistical analytics. It also creates charts and reports that help us analyze that data.

It can also create design blueprints for anything from buildings to new devices. When combined with technology such as 3D printing or automated construction robots, it can create physical objects that exist in the real world.

Generative AI Doesn’t Need Human Input

When we think of generative AI output, we might think that everything is fully automated and that humans aren’t necessary. But this is far from the truth, today at least.

For a start, generative AI often makes mistakes or just plain makes stuff up – a phenomenon known as hallucination. For any critical use case, it’s essential to involve human oversight for fact-checking and error correction.

Human input is also necessary at every step of the process to ensure that AI is being used in a way that’s fair, ethical and responsible. This is particularly important when AI is put to work in ways that can affect human lives, for example when making decisions in the fields of healthcare, finance, human resources or law enforcement.

While generative AI can be an extremely powerful and useful tool, it’s nowhere near being good enough to fully replace human judgment and expertise.

Generative AI Is New

It may seem like generative AI burst into the world with the arrival of ChatGPT in late 2022, but that was really just when it hit the mainstream. People have been using AI to create things – including text, pictures and music – for far longer.

The first experiments with AI chatbots took place in the 1960s, with programs like Eliza that tried to hold human-like conversations. Early examples of AI-generated music emerged in the 1970s, like David Cope’s Experiments in Musical Intelligence, which aimed to mimic the style of famous composers. And AI image generators first appeared in the early 1990s, such as AARON, created by artist Harold Cohen. And

What’s new is that we’ve now reached the stage where a combination of factors, including availability of processing power and computer memory, cloud computing and advances in deep learning have made generative AI available to everyone.

Rather than needing expensive computers that were only previously available to big companies and universities, we all carry smartphones that can hook up to massively powerful data centers in the cloud, where the computing takes place. This means generative AI is best seen as a convergence of many technologies that have all matured at this point in time to kickstart the revolution rather than one breakthrough invention.

Do you remember what the internet of the past looked like? Static webpages that took an age to load, blurry JPG images and lots of garishly colored text and backgrounds, those were the days!

Well, the internet of 2035 will look as different from today’s internet as today’s internet looks from that.

In the twenty-plus years that it has dominated our lives, the internet has evolved to become more immersive, accessible, user-friendly and social. Although it’s difficult for anyone to predict anything as far as ten years into the future, one thing I’m sure of is that this evolution will continue.

Ten years ago, if you’d asked someone what the internet is, they would have been pretty sure it revolved around web pages viewed on a computer screen. Today, the online experience is built around apps, devices, streaming services and virtual worlds. Thanks to advances in augmented reality (AR), we even see it encroaching into the real world.

So, gazing into my long-distance crystal ball, here are five of the trends that I believe will define what it means to be “online” as we head toward the year 2035. And – spoiler alert – yes, there will probably still be cat memes.

Reality? What’s That?

Over the next decade, we are only going to see the internet get more immersive and capable of filling more of our day-to-day needs. Whether that be working, relaxing, playing, shopping or socializing with friends. By 2035, the concept of “being offline” probably won’t mean a lot. Even if we aren’t staring at a screen (an interface that’s becoming less common), we’re interacting with virtual and online environments through data flowing to us via a myriad of devices, possibly even including chips implanted into our brains.

It’s no wonder that by this point, the distinction between the real, physical world and the digital, connected world is practically non-existent. Augmented reality interfaces will bring digital information to life in front of our eyes, overlaying computer-generated imagery no matter where we are or what we are doing. And the concept of logging or signing in to a virtual space will seem wildly outdated, as machines automatically authenticate us using biometrics without us even noticing. This will put to bed the idea that’s persisted for a few decades of humans becoming increasingly screen-bound, isolating inside darkened rooms or existing in virtual reality, Ready Player One style. The internet and the virtual world will be all around us, entwined with the real world – which is perhaps an even scarier concept!

An End To Ecosystems?

So Meta (formerly Facebook)’s attempt to annex the emerging virtual domain that we once referred to as “the metaverse” (although I never liked that term myself) seems to have stalled. In 2024, users want virtual worlds – not walled-in virtual gardens – and in 2035, that won’t be any different. Rather than be tied into any particular ecosystem – be that iPhones or Android, Xbox or Playstation – users will expect cross-platform compatibility and seamless connectivity, no matter what hardware or operating system is chugging away behind the scenes.

This means, for example, that users will be able to take their avatar from Fortnite, along with the trophies and rewards they’ve gained, and effortlessly manifest them into Roblox. For a slightly more grown-up example, think of your Slack or Zoom conversations and contacts seamlessly integrating into MS Teams – or whatever equivalent of these tools we’re all using in 10 years’ time.

This might all be facilitated by a move towards open, decentralized ecosystems – perhaps built on blockchain technology – as more of us become aware of the dangers of giving companies like Google, Microsoft and Apple ownership of our online lives and identities.

Virtual Healthcare

It is becoming increasingly common for us to go online to receive medical care or treatment. Contributing factors include the coronavirus pandemic, aging populations and the worldwide shortage of medical professionals.

All of this will mean that online healthcare will be a big part of our lives by 2035. Patients and healthcare providers will meet less frequently but be more closely connected than ever, thanks to the wealth of data that will be collected by devices we wear and even cameras in our homes (watching for declining activity levels in elderly people or falls in the home, for example.) Many more of us will experience time as patients in a virtual hospital, where we will be closely monitored and receive personalized care in the comfort of our homes.

At the same time, all of this data will be used to build increasingly sophisticated digital twins of our bodies, meaning that treatment will be personalized and targeted at our specific conditions. Questions around healthcare data and who owns the information about our condition and wellbeing will be more prescient than ever, but solutions based on blockchain and decentralized record keeping may help us retain control and stewardship.

One major benefit will be that we are no longer tied to receiving care from experts in our locality or making long and costly journeys to be treated by experts around the world. And VR or AR will mean we can be treated online for many of our pain management, mental wellness or physiotherapeutic needs.

Virtual Economies And Digital Ownership

By 2035, virtual products and goods will be just as desirable and in demand as the most limited edition sneakers or VIP Taylor Swift tickets are today. And why shouldn’t they be? To the teenagers of tomorrow, bragging rights will apply to possessions in the digital domain as much as they do in the physical.

From virtual real estate to digital certificates and collectibles, these assets will hold real-world value, creating new economies and transforming online business, gaming and socializing. This will foster the development of new business models, providing virtual goods and services as well as access to online events like virtual concerts and experiences. The creator economy that we are already seeing develop around platforms like Roblox will be a bigger part of our lives. Much of this will be thanks to the democratization of digital creativity enabled by generative AI and emerging low-code/no-code tools. This has the potential to increase access to opportunity, allowing individuals from diverse social and economic backgrounds to participate in building the future of online experience.

credit: BarnardMarr

Thanks to AI, work will look very different in the near future than it does today. According to the World Economic Forum, 85 million jobs will be impacted by AI by 2030, and millions of new jobs will be created that don’t yet exist.

In a world where the pace of change is accelerating dramatically, it will be our skills -rather than our education, work history or past achievements – that define our value.

In practical terms, employers will be less concerned about what we know or have achieved in the past and more interested in how we can apply knowledge and abilities to solving modern business challenges.

So, what will this mean in the age of AI? How do we prepare for a world where machines will carry out many of the tasks that humans have traditionally had a monopoly on? And what skills will we need to ensure we remain relevant and able to create value? Let’s take a look.

Two Core Skillsets For An AI Future

I believe the skills essential for staying relevant in the future can be divided into two groups. Broadly speaking, we can refer to these as AI skills and human soft skills.

Firstly, having AI skills doesn’t necessarily mean becoming an AI engineer or data scientist.

Instead, it involves the ability to use AI effectively, augmenting our own abilities and overseeing its output. This means becoming an effective AI collaborator, delegator, and supervisor.

As AI becomes increasingly omnipresent, the ability to identify and use the best tools will be crucial in virtually every profession.

Secondly, human soft skills represent abilities that AI either can’t do yet or can’t do as well as humans. These skills are rooted in the qualities that have made humans so successful as a species in evolutionary terms. They allow us to work together, solve complex problems using diverse data, navigate social situations, creatively solve problems, critically evaluate progress, and create emotional connections with others.

As machines become more capable, the value of these uniquely human abilities increases. These two skill subsets are complementary, and developing them in tandem is key to building future-proof skills.

Let’s explore each of these skill sets in more detail.

AI Skills

AI skills are a broad category encompassing everything that has to do with working with AI effectively.

Of course, it includes the technical data and computing skills needed to design, build and deploy AI systems. But not everyone will need to do that.

It also covers general AI literacy, which means understanding what AI can do and how to apply AI tools to achieving specific goals.

This involves understanding the AI landscape in terms of the available tools and applications, and their capabilities and limitations, as well as proficiency in using and operating these tools.

It covers skills such as prompt engineering, which involves being able to frame human and business problems in a way that AI can address.

A central concept is “augmented working” – a term that’s frequently used to describe the ability to use AI to automate routine tasks, allowing a human professional to work more efficiently.

Understanding how to use AI to aid and boost creativity is a valuable skill, too. This could involve using it to generate ideas or create multiple iterations of our own ideas to suit different audiences.

People with skills needed to supervise AI workforces and act as the critical “human-in-the-loop” required to ensure accuracy, safety and fairness will be highly valued in workforces of the future.

Crucially, so will those with an understanding of the ethical and legal implications, such as an ability to recognize when there is a danger of bias or breach of privacy or when an organization’s use of AI might be overstepping the boundaries set out by regulation and legislation.

Soft Skills

With AI taking care of much of the technical work, human soft skills – things that machines can’t yet do – will become exponentially more valuable.

Among the most important will be the ability to strategize at a high level.

For example, ask an AI delivery optimization algorithm to plot the most efficient route for a van driver to drop off parcels, and it will do it more effectively than a human.

What it probably won’t do is suggest exploring drone delivery. Or reducing the weight of packaging to make deliveries more fuel-efficient. This is because most AI applications are highly specialized and don’t have the “general” intelligence capabilities of humans.

Creative problem-solving is another vital soft skill. Humans excel at lateral thinking, connecting disparate ideas, and imagining novel solutions to complex problems. Our ability to envision and articulate a better future – whether in technology, society, or the environment – is uniquely human. This imaginative capacity, combined with the power to inspire others towards these visions, will remain crucial in an AI-driven world, allowing us to conceptualize and pursue innovations that AI alone cannot conceive.

Developing plans that encompass long-term goals and take into account a multitude of factors that aren’t necessarily going to be in the training data will be out of reach of AI for a long time.

Then there’s critical thinking, which involves objectively analyzing and evaluating every aspect of a problem, situation or opportunity in order to make a judgment. While AI can critically assess a plan of action or an idea, once again, it’s limited by its training data, which may or may not contain the specific insights required.

Teamwork, leadership and mentorship all require explicitly human skills, too, including a high level of emotional intelligence. This is our ability to recognize and respond appropriately to our fellow humans on an emotional level and is essential to collaboration and relationship-building.

Partnership building, for example, is critical in modern business. An AI’s lack of emotional intelligence means it will always be at a disadvantage when it comes to the subtleties of negotiating, building rapport, and establishing the alignment of mission and values, which are critical to effective partnering.

And human soft skills are still important for project management, where there’s a need to balance resources, budgets, time constraints and any number of unexpected factors that could emerge.

Once again, we can see that computer intelligence is still too specialized to deal with many potential scenarios that can throw a spanner in the works of even the most carefully laid plans.

Adaptability and Life-Long Learning

One skill, perhaps more than any other, that will determine whether we remain relevant in the AI era will be our ability to adapt to change and continuously learn and improve.

Technology is constantly evolving, and the AI available in ten years’ time will most likely be far beyond anything we can imagine now. No matter how carefully we prepare for it now, it will take us by surprise. So, the ability to adapt and keep our knowledge and skills up-to-date is crucial.

This isn’t just about keeping pace with technology; it’s about developing a change-oriented mindset that will allow us to continue to perform as the world becomes more complex and uncertain.

The tradition of front-loading ourselves with education in our formative years is increasingly outdated. Seeking out roles where we will continuously learn, as well as pursuing opportunities for self-directed learning, can all help us to develop this mindset.

Likewise, the human skills we’ve discussed – communication, creativity, emotional intelligence – are not innate traits that some are born with and some aren’t. They can all be cultivated through practice and diversity of experience!

By focusing our efforts on developing both human and AI skills and developing the habits of embracing change and lifelong learning, we can give ourselves the best chance of thriving in the age of AI.

source: benardmarr

Artificial Intelligence (AI) has been making waves for years, but it’s the subset of generative AI that’s really captured the public’s imagination lately. If you’ve been anywhere near the internet in the past year, you’ve probably heard of ChatGPT, DALL-E, or perhaps Midjourney. But what exactly is generative AI, and which model stands out as the most famous?

Let’s dive in.

The Generative AI Revolution

Generative AI refers to artificial intelligence systems capable of creating new content, whether it’s text, images, music, or even code. These AI models learn from vast amounts of existing data to generate something new and original. It’s like teaching a computer to be creative – and boy, have they learned fast!

The Reigning Champion: OpenAI’s GPT

When it comes to fame in the generative AI world, one name towers above the rest: GPT (Generative Pre-trained Transformer) by OpenAI. This powerhouse of a model is the brain behind ChatGPT, which has become something of a celebrity in its own right.

But why is GPT so famous? Let’s break it down:

1. Pioneering Innovation: GPT was among the first to showcase the true potential of generative AI in a way that was accessible to the public. It turned what seemed like science fiction into reality.
2. Versatility: From writing essays, speaking and creating images to debugging code, GPT’s range of capabilities is staggering. It’s like having a Swiss Army knife of AI tools at your fingertips.
3. Mainstream Adoption: By making ChatGPT freely available, OpenAI democratized access to advanced AI. Suddenly, everyone from students to CEOs was experimenting with AI-generated content.
4. Constant Evolution: With each iteration (GPT-3, GPT-4, and beyond), the model has become more powerful and capable, continually pushing the boundaries of what’s possible.

The Contenders

While GPT might be the most famous, it’s not the only player in town. The generative AI landscape is teeming with impressive contenders:

• Google’s Gemini: A strong rival to GPT, offering multi-modal capabilities and impressive performance.
• Anthropic’s Claude: Known for its focus on ethical AI development and robust conversational abilities.
• Meta’s LLaMA: Facebook’s parent company has thrown its hat into the ring with this open-source large language model.
• Stability AI’s Stable Diffusion: A go-to for many in the image generation space.
• Microsoft’s Copilot: Integrating AI assistance across the Microsoft ecosystem.

Each of these models brings something unique to the table, but GPT’s head start and widespread adoption have cemented its place at the top of the fame ladder.

The Impact And Implications

The rise of GPT and its generative AI buddies has sparked a technological gold rush. Companies are scrambling to integrate these technologies into their processes and their products and services. We’re seeing AI-powered writing assistants, code generators, and even AI therapists hitting the market.

But it’s not all smooth sailing. The rapid advancement of generative AI has also raised important questions about copyright, job displacement, and the spread of misinformation. As these models become more sophisticated, distinguishing between AI-generated and human-created content is becoming increasingly challenging.

What’s Next For Generative AI?

The field of generative AI is evolving at breakneck speed. We’re likely to see even more powerful and specialized models emerge in the coming years. The integration of generative AI into our daily lives – from personalized education to advanced healthcare diagnostics – is just beginning.

As for GPT, its fame shows no signs of waning. With OpenAI continually pushing the envelope, we can expect future iterations to be even more capable and, dare I say, mind-blowing.

The AI-Powered Future

While GPT currently wears the crown of fame in the generative AI world, the competition is fierce and the landscape is constantly shifting. What’s clear is that generative AI is not just a flash in the pan – it’s a technological revolution that’s here to stay.

As we navigate this brave new world of AI-generated content, one thing’s for certain: the most famous generative AI of today might just be the tip of the iceberg. The real excitement lies in imagining what these technologies will be capable of tomorrow. So buckle up, the AI ride is just getting started.

credit: Berdard Marr

As artificial intelligence continues to reshape industries, understanding which jobs remain secure is crucial. While AI’s impact on the job market is undeniable, not all roles are equally vulnerable. Most jobs will be augmented to some extent, but those involving complex human emotions, advanced decision-making, and creative thinking are generally safer from complete automation. Here are some of the most AI-resistant careers:

Skilled Tradespeople

Skilled tradespeople, such as electricians and carpenters, possess hands-on expertise and problem-solving skills that AI cannot replicate. These roles require working in varied environments, adapting to unique challenges, and applying practical knowledge in real-time. The physical dexterity, spatial awareness, and on-the-spot decision-making needed in these trades make them resilient to automation. While AI can assist with tools and planning, the nuanced skills of a tradesperson remain irreplaceable.

Healthcare Professionals

Healthcare professionals, including doctors, nurses, and therapists, are essential roles that AI can only partially augment. AI can assist in diagnostics, patient monitoring, and even robotic surgeries. Still, the core of healthcare revolves around human empathy, interpersonal skills, and ethical judgment—qualities that AI cannot replicate. Understanding patient needs, providing compassionate care, and making critical ethical decisions ensure that healthcare professionals remain indispensable.

Strategic Decision-Makers

Executives and entrepreneurs occupy roles requiring high-level strategic decision-making and leadership capabilities. These roles involve understanding complex, multifaceted problems, weighing risks and benefits, and making decisions that steer organizations toward success. While AI can provide data-driven insights and assist in analysis, the nuanced understanding of business dynamics, stakeholder interests, and long-term vision are uniquely human attributes safeguarding these jobs from automation.

Creative Professions

Creative professionals, such as artists, writers, and designers, bring originality and a personal touch to their work that AI struggles to match. Generative AI tools can perform simple creative tasks and even assist in the creative process, but the essence of creativity involves inspiration, cultural subtleties, and deep emotional connections. The ability to convey human experiences, emotions, and unique perspectives ensures that creative professionals remain at the forefront of their fields, with AI serving as a supportive tool rather than a replacement.

Emergency Responders

Emergency responders, including firefighters, paramedics, and police officers, perform roles demanding quick thinking, human judgment, and physical presence. These jobs require the ability to assess unpredictable situations, make life-saving decisions, and provide immediate assistance. The complex and dynamic nature of emergencies is beyond the capabilities of current AI technologies. The physical and emotional demands placed on emergency responders highlight the irreplaceable value of human skills in these critical roles.

Embracing Uniquely Human Skills

The roles mentioned above emphasize human interaction, emotional intelligence, and creativity—qualities that AI can’t replicate yet. As AI continues to evolve, it’s essential to focus on developing and enhancing these uniquely human skills to stay ahead. By leveraging our innate abilities in empathy, strategic thinking, and creativity, we can ensure a harmonious coexistence with AI and secure our place in the future job market.

While AI will continue to augment and transform various aspects of work, the importance of human expertise, intuition, and emotional intelligence remains paramount. Embracing change, continuously learning, and adapting to new technologies will be key to thriving in an AI-enhanced world. By understanding the roles that are most resistant to automation, we can better prepare ourselves and future generations for a dynamic and ever-evolving job market.

So, what job is most safe from AI? It’s the ones that require the irreplaceable touch of human skills—those that make us uniquely human.

Credit: bernardmarr