SMART moves – how to design work in the age of AI

Successful adoption of AI requires a human-centred approach that enhances and extends human capabilities for the good of people and businesses, writes Daljit Singh.

In short:

• ‘Well-designed’ work has the capacity to improve business outcomes, while also promoting employee performance and wellbeing.
• While AI can complement smart work approaches, a top-down “technocratic” approach to such technology can lead to anxiety and reluctance among employees around its adoption.
• By contrast, a human-centred approach to AI adoption can empower employees and unlock economic value for organisations.

The race by many legal organisations to gain a competitive advantage in the age of AI will increasingly place the design of work at the core of their talent strategies.

This article describes what constitutes well-designed work, explores potential challenges to work that are likely to be posed by the adoption of AI, and discusses how to overcome these through a human-centred approach to AI, alongside the right leadership mindset.

What is well-designed work?

There is a considerable body of research and evidence focusing on well-designed work that promotes both employee performance and wellbeing. The salient elements of this research have been captured by Professor Sharon Parker and her colleagues from the Centre for Transformative Work Design, in their SMART work design framework.

This framework describes the work characteristics that lead to positive employee and organisational outcomes, including:

• greater employee engagement
• increased creativity and innovation
• higher levels of performance
• improved wellbeing
• reduced attrition.

There are five key elements of work in the SMART framework:

• Stimulating – work that includes a variety of skills and tasks, and is challenging
• Mastery – work that develops competence through feedback from the job and other people, and provides clear roles and responsibilities
• Agency or autonomy – work that offers control over how and when it is done and in making decisions
• Relational – work that provides a sense of belonging, co-worker and supervisor support, and positively impacts others
• Tolerable demands – work that has manageable time pressure and deadlines, and few conflicting demands.

Potential challenges to work by the adoption of AI

There is increasing recognition that while AI can have a positive impact through the elimination of routine tasks and the augmentation of human capability, it can also have significant negative impacts on work as follows:

• Stimulating – AI adoption may narrow the variety of work tasks and associated skills requirements
• Mastery – extensive automation may reduce the ability of people to develop skills and judgement and reduce their sense of competence
• Autonomy – AI solutions may take decision-making ability away from people and reduce their sense of agency at work
• Relational – AI may reduce the interactions that people have around tasks that become automated
• Tolerable demands – AI adoption may lead to an expansion rather than a reduction of work demands, especially in ‘always on’ work cultures.

These potential negative impacts are likely to arise when organisations take a purely technocratic approach to AI adoption through top-down driven AI solutions that disregard their impact on the quality of work experience. This technocratic approach can create anxiety in people and lead to their reluctance to embrace AI.

A more successful approach to AI adoption requires a human-centred approach, which aims to enhance and extend human capabilities for the good of people and the business.

Research demonstrating the success of the human-centred approach includes a report by Ellyn Shook and Paul Daugherty from Accenture, titled ‘Work, Workforce, Workers: Reinvented in the Age of AI’, which concludes that it provides the most benefit to people, as well as unlocking the greatest economic value for organisations.

Using the human-centred approach for adopting AI

The human-centred approach places human needs, values and capabilities at the core of AI adoption such that redesigned work enhances human capabilities and wellbeing, rather than diminishing them.

It involves closely collaborating with people to decide how best to use AI, by automating more routine tasks and augmenting human capabilities.

A four-part framework to guide the process for the human-centred adoption of AI is presented below. This draws on the work of Nichol Bradford, a global thought-leader on human-AI collaboration, and offers practical suggestions for adopting AI.

1. Empower – develop a vision for adopting AI by engaging with people. Ask people how AI can help them enhance their performance while also better serving clients. For example, by:
   • removing inefficiencies in workflows
   • reducing what they dislike doing
   • enabling them to do more of what they like doing, including higher-value work.

2. Steward – establish ethical guidelines of responsible AI aligned to organisational values and societal norms. For example, by:
   • establishing principles for using AI such as ensuring transparency, fairness, accuracy, data privacy and preventing bias
   • helping people to understand how AI can potentially affect their work, using the elements of the SMART work design framework, and working with them to ensure that these remain integral to their work.

3. Explore – encourage experimentation and collaboration across the organisation. For example, by:
   • creating a psychologically safe environment for people to experiment and innovate with AI
   • encouraging the sharing of insights and learning to redesign work and workflows, including identifying new higher-value tasks and the tasks to be automated (AI), augmented (people and AI) or done solely by people.

4. Activate – build workforce readiness. For example, by:
   • generating trust through all of the above and by providing people with all of the information, support and reskilling and upskilling opportunities to succeed
   • reinforcing that a key role of AI is to help people grow their capability, enhance their wellbeing and expand their potential opportunities.

Using a human-centred approach based on the principles of well-designed work will ensure that we help people to thrive in the age of AI, enabling them to do more engaging, meaningful and higher-value work.

Legal organisations should also engage with their leaders to explore their prevailing mindsets regarding people and work, and shift these if needed. 

Shifting leadership mindsets

The Deloitte Global Human Capital Trends 2024 report states that many organisations are stuck in a legacy mindset centred on extracting value from people, rather than collaborating with them to create a better future for organisations and individuals alike. It noted that a ‘human sustainability’ mindset should replace the extractive mindset.

The table below contrasting these two mindsets has been adapted from my article last year in this journal, titled ‘Advancing Human Sustainability in the Age of AI’.

We can see that the extractive mindset promotes opportunistic, short-term thinking and actions, with performance being achieved at the expense of people. In contrast, the human sustainability mindset promotes strategic, long-term thinking and actions, enabling people and performance to thrive, consistent with the principles of well-designed work and the human-centred approach to AI.

The global wellbeing crisis in the legal profession, as revealed by surveys conducted by the International Bar Association and several national legal associations, indicates that the extractive mindset is likely to be the default mindset in many legal organisations. If unchallenged, it will be this mindset that will drive AI adoption and work.

Fortunately, there are constructive ways to help assist organisations shift leader mindsets. ‘Vertical Growth’, by Bunting and Lemieux, is an excellent guide for facilitating mindset and behavioural change, with helpful diagnostic tools, practices and case studies.

Conclusion

Using a human-centred approach based on the principles of well-designed work, as well as having leaders with the right mindset, will be critical for the successful adoption of AI. Legal organisations that get this right will get an affirmative response to the questions below:

• Stimulating: Will our people experience a variety of work tasks, use of skills, and do challenging work with the adoption of AI?
• Mastery: Will our people grow their sense of competence through AI augmenting their capabilities?
• Autonomy: Will our people understand how AI really works in the background, and can they override it if required?
• Relational: Will our people feel that they belong and are supported through quality human interactions in an AI-enabled work environment?
• Tolerable demands: Will our people feel that the adoption of AI will protect their wellbeing through sustainable work demands?

Legal organisations must seize the opportunities and mitigate the challenges in the age of AI to create more positive employee and organisational outcomes, enabling both them and their people to thrive in the emerging new world of work.

Daljit Singh is the Principal of Transforming Talent. He is a talent management and leadership development expert and has held senior roles with KPMG and Baker McKenzie. Daljit is also a Teaching Fellow with the Australian College of Law where he teaches two post-graduate subjects – Workforce of the Future, and Leadership. You can contact him at daljit.singh@transformingtalent.com.au

References

• Bradford, N. (2025), Empowering Employees to Unlock AI’s Potential. Society for Human Resource Management.
• Bunting, M. with Lemieux, C. (2022), Vertical Growth – How Self-Awareness Transforms Leaders and Organisations. Wiley.
• Deloitte Insights (2024), Global Human Capital Trends – Thriving Beyond Boundaries: Human Performance in a Boundaryless World.
• Legal Policy & Research Unit (2022), IBA Young Lawyers’ Report. International Bar Association.
• Mayer, H., Yee, L., Chu, M. and Roberts, R. (2025), Superagency in the Workplace: Empowering People to Unlock AI’s full potential. McKinsey Digital.
• Parker, S.K. and Knight, C. (2025), Design Work to Prevent Burnout. Vol. 66, No.2, MIT Sloan Management Review.
• Parker, S.K. and Grote, G. (2022), Automation, Algorithms, and Beyond: Why Work Design Matters More than Ever in a Digital World. Applied Psychology, 71(4), 1171-1204.
• Valentine, M., Hancock, B. and Weddle, B. (2023), Human-Centered AI: The Power of Putting People First. McKinsey.com.
• Scoble-Williams, N., Sinti, D. and Vert, G. (2023), Generative AI and the Future of Work. Deloitte AI Institute.
• Shneiderman, B. (2022), Human-Centered AI. Oxford University Press.
• Shook, E. and Daugherty, P. (2024), Work, Workforce, Workers: Reinvented in the Age of AI. Accenture.
• Singh, D. (2024), Advancing Human Sustainability in the Age of AI, Australasian Law Management Journal. Law Council of Australia.