Throughout human history there have been paradigm shifts in society, science and commerce that have triggered revolutions in how human beings engage with technology. Such revolutions or paradigm shifts can be understood with the Emerging Paradigm Model (EPM) (Smith and Rasool, 2015); (Bienert et al., 2016). The cyclic nature of paradigm shifts in the EPM is illustrated in Figure 1. The EPM recognises that paradigm shifts in history happened through shifts in mindsets followed by the mindsets being embodied in practices or techniques and finally technology being brought in to scale and refine the way things are done and the dissemination of the practices and underlying mindsets. Paradigm shifts in the last few hundred years have manifested as Industrial Revolutions.

Revolutions typically begin with one or more people thinking differently than the status quo, they form new mindsets through which to frame disciplines. For those seeing merit in the mindsets, techniques and practices are developed to prove the mindset’s value. Valuable practices and methods will test the integrity of the mindset and if it has too many flaws it could be abandoned but if it proves to be robust enough to be useful it can be adopted or integrated in existing working contexts. To scale the adoption or dissemination of practices related to the mindset, technologies can either be created or re-purposed for reaching wider and broader audiences or markets as well as sustaining quality through continuous refinement. The technologies, if coupled well with practices, can reveal their shortcomings, inferring the call for more refined methods. The technologies could even reveal that an apparently robust mindset that many had been practicing could have subtle or nuanced flaws, possibly leading to it being advanced. This suggests the process of revolutions arising through new mindsets, techniques and technologies is not linear but circular, operating in a cycle, where new technologies, if sufficiently advanced can result in the emergence of new mindsets.

Along with Industrial revolutions, parallel sets of stages in development and revolution of coaching have happened (Passmore and Woodward, 2023). The phases are 1) “pre-profession,” transactional and unqualified training and delivery of coaching 2) “practice-based professionalisation,” a movement into qualification and competency based coaching provision with governing body oversight and 3) “evidenced-based professionalisation,” growth through higher education programmes and evidence-based research driven training. From the mid-2020s a shift in the coaching industry happened from “professionalisation” to “productisation,” where coaching was packaged in a scaled way through online digital coaching platforms.

Another perspective is the evolution of workplace coaching development (Grant, 2016). Workplace coaching for employees, managers and leaders focuses on helping them attain work-related goals. Over the last 30 years, three generations of workplace coaching have been progressed through. From the 1990s, the first generation’s focus was performance management. From the 2000s, the second-generation utilised coach training programmes, with a methodical, sequence of steps, to enable leaders to augment their function with coaching approaches. This mechanistic approach through did not align in its fit with organisational environments where uncertainty and rapid change were the norm. From 2010 onwards, a third “generation” workplace coaching approach evolved that would align well with future Industry 5.0 mindsets. It involved a harmonised enhancement of both the performance and the wellbeing of individuals and organisations in ways aligned with Industry 5.0 strategies that cultivate sustainability and employee flourishing alongside technology augmentation, automation, adaptation and adoption.

Industry 5.0 mindsets seek to harmonise human and technology sourced intelligence, and their reciprocal, mutual development. Auditing what intelligences must be cultivated and which ones must coherently exchange development will be primary areas of concern for coaches guiding those in Industry 5.0 shaped workplaces. A variety of human, technology and hybrid intelligence strategies may be needed (Kolbjørnsrud, 2024). These include.

• Individual intelligence: when a human individual works independently (without intelligent technology).

Industrial revolutions, coaching developmental stages and intelligence approaches have refined how data, information, knowledge, intelligence and wisdom are managed through empowered training, learning and development as well as coaching approaches, something framed as early as 2010 by the author and discussed in the next section.

The illustration, Figure 3. shows how, historically, the raw assets of eras in computing have shaped technologies, especially the evolution of social networking relationships (Rasool, 2010). The very first kinds of data were purely handled by hardware, with Charles Babbage’s Difference Engine, and later, solid state electronics. Data was organised into information and visualised across Data networks through browsers like Mosaic and Netscape, focusing on creating an internet that connected people through data that had relevance, the era that could be considered “Web 0.0.” That organisation of networked data into information was no longer done purely by hardware but software, so this was the era of the Software, Relevance driven Internet. Web services like Yahoo, Google and Wikipedia would then organise that networked information into Knowledge, in the essential era of Web 1.0 at the turn of the 21st century. Around this time Networked Knowledge started to be organised into Networked relationships and social intelligence, especially through platforms like Facebook which would work on a Relevance driven internet influenced by what people had a resonance with. This was a time of Web 2.0, where Social Networking and human connections fostered Cloud based services and a Cloud driven Internet. The outcome of this would be emerging era of Intelligence assets. Around 2008, the author recognised the need for a new kind of web engine that optimised for resonance-based connections that delivered outputs that were of relevance to users. This Web 3.0 era saw the creation of the first Resonance Engine that organised networked relationships, and collective consciousness, into applied networked wisdom and action. This era, the one we are at the peak of now is where Cloud based technologies are giving rise to what was called “Mindware”at the time the illustration was first designed in 2010. Mindware in current parlance, is what people are now engaging with in the form of technologies such as Generative AI, including applications that simulate varieties of human conversation as if users were exchanging with human minds.

A key lesson to be learnt through this evolutionary process is that Data is not Information, Information is not Knowledge, Knowledge is not Intelligence, Intelligence is not Wisdom, Wisdom is not Action and Action is not Impact or Power. For coaching, the challenge for the future will centre on converting Intelligence into Wisdom, Action, Impact and then the kind of Power that results in Empowerment driven realisation of potential, talent and performance.

However advanced technologies like AI get, there is no guarantee they will trend towards generating empowering wisdom. So, to have AI advance human wisdom it is important to look at what AI is currently capable of and see how it compares with what a human coach might be able to achieve with a client.

How well AI can coach human beings can be evaluated through four spectrums (Rasool, 2024a) of characteristics that frame coaching progress, Rapport, Change, Development and Confidence as seen in Figure 4.

Passmore et al. (2024) suggest in their report that digital and AI coaching is transforming organisational and business practices. The report explored attitudes towards Digital and AI augmentation of Coaching from a Global Coach survey undertaken in Summer 2023. These perspectives suggest that businesses are adapting operations so that they can.

• Leverage AI for scaling and improved efficiencies: AI tools can be uses to reduce costs, facilitating scalability as well as improve efficiency of delivering coaching services.

These can be considered a sequence of adaptation, integration and adoption phases. Such trends can help businesses strategically bring AI into their operations, ensuring there is proof of value for each people/technology ecosystem. How this unfolds over the next decade will need to be closely watched by governing bodies of coaching and appropriate coaching competencies evolved so they are not just suitable for human-to-human coaching but also fit for use with AI Coach to Human Client scenarios.

Diller et al. (2024), looked through a survey at how business coaches feel about the rising use of AI in business coaching services. Specifically, how artificial intelligence is integrated into business coaching opportunities, offers improvements in efficiencies related to costs and time management. However, there were concerns about the risks and challenges that were posed. Professional service workers, like business coaches, felt their role and value in business environments might be at risk or undermined.

Coaching is not available to everyone because of cost issues and availability. Divides exist that hinder Democratisation of Coaching (Bachkirova and Kemp, 2024). AI approaches can help, augmenting, to various degrees, some elements in human coaching but these also suffer from the challenges of the Digital Divide between those that have access and those that do not, so for Coaching to be democratised, AI needs to be democratised.

A danger of using AI as an affordance, adaptation or adoption is that it will be used whenever ethical conscientiousness is low, or it is referred to for convenience when desire to critically think or be creative is low, possibly leading to muscles of competence and discernment undergoing atrophy. Despite the myth, Peter Drucker never said, “Culture eats strategy for breakfast” (Tallman et al., 2021), but a similar meme is emerging. People may well use AI for the sake of convenience at the expense of competence that fails to be exercised, resulting in the author’s frame of this trend, “Convenience eats competence for breakfast”, possibly becoming a future meme. The danger emergent from these behaviors is sourced from a lack of applying Ethics due to complexity of dilemmas to be considered.

This calls to attention the need to ensure technologies, especially AI, are used ethically. The EU AI Act cites unacceptable, high, medium and low levels of risk categories that people could be exposed to for which mitigation strategies must be implemented. Of the eleven risks identified in the unacceptable and high categories, nine are likely to be ones that coaches and clients will be exposed to. Ethical dilemmas will arise relating to transparency, accountability, integrity of data, privacy, client and user autonomy, diversity, accessibility, adaptability, and flexibility (Diller, 2024).

Dilemmas will require enforceable monitoring, oversight, governance and professionalisation if not regulation. If the required governance is not crafted and implemented by governing bodies in coaching, regulation may inadvertently be forced through if harm is brought about by coaches using AI systems by failing to implement national and international legal regulations such as those in the EU AI Act. Insurers have indicated that under such situations, coaches may find any claims brought against them might not be supported, the premiums for Professional Indemnity and Liability Insurance might be increased, the insurance policy could be voided, or the coach may find no insurer will provide further new cover if previous liability claims were considerably egregious in their nature, consequences that could end a coach’s ability to practice, even ending their careers.

There are dangers and dividends or risks and rewards to adopting technologies to enhance coaching practice. They must be audited by practitioners, coaching schools as well as governing bodies. What has benefit needs promotion, what might bring harm must be regulated for. Industry 5.0 practices applied to coaching can ensure human beings develop and advance in concert with technologies being adopted, developed and advanced.

If humans are not supported, through Industry 5.0 approaches to Coaching, Coaching 5.0 practices, they will not be fit enough to take advantages of technology affordances, and we may see workforces diminish in their competence. With collaborative, reciprocal development, human beings and technologies can advance workforces, workplaces, societies and even humanity.

This paper highlights that the future use of AI in coaching will not just require assurance of equitable human access, affordances and accommodation but also appropriate adaptation, integration and adoption with existing people and technology ecosystems in businesses and organisations, through operationalised Industry 5.0 mindsets, techniques and technology infrastructures.