How Your AI Strategy Can Create a Low Performance Culture.

Ⓒ 2026 Martin Tynan     email: martin@newtribeconsulting.com

Summary

Introduction

McKinsey’s 2026 Global Survey on the State of AI provides some interesting data points. One unsurprising datapoint is that of over 1,700 organisations surveyed across 97 countries, 89% of organisations surveyed use AI in at least one business function (this is only 1% up from last year). Perhaps the more surprising datapoint is that the same report shows only 6% of organisations surveyed have seen meaningful financial impact from AI at an organisational level (this is unchanged from the 2025 survey). Using this survey as a datapoint, with 89% of organisations surveyed using AI and only 6% seeing any meaningful financial impact, it is safe to say that, to date, the impact of AI investment in organisations has been underwhelming. Most commentators agree this gap will close, but how?

One prevailing view is that the investment in AI will replace the cost of employees. However, It is challenging to get a clear picture of this, as it is hard to differentiate between organisations that are cynically using AI as an excuse to lay people off (when the actual reason is otherwise) and those organisations, where employee layoffs are a direct result of AI performance gains.

Interestingly, given the apocalyptic predictions of how AI will decimate the workforce, two-thirds of respondents in the same survey reported no change in headcount related to AI initiatives. The workforce apocalypse has not yet happened ( (although it is interesting to note the mildest whiff of disappointment around this from the more extreme AI evangelists).

However, what is emerging from the data is a very clear direction of travel on where investment dollars are going. In a 2025 survey by Deloitte (published in 2026), 93% of investment in AI in companies surveyed went directly to technology and tools, and 7% went to organisational capacity to create value from this, like training, change management, culture etc. (Deloitte, The AI Investment Trap, 2026). Thus the investment balance seems pretty skewed towards technology over people.

The purpose of this article is to explore (not predict), an in the moment, high level assessment of where organisations are today on their AI journey from a cultural and a people perspective, And how some of the experiences and the data over the last couple of years might provide some insight into how organisations can look at ways to significantly close the gap between 89% usage and 6% meaningful impact of AI in organisations.

This article argues that it is perhaps individual employee’s mindset towards the introduction, adoption and positioning of AI in companies which might be one of the key factors to explain this gap. And perhaps a rebalancing of organisational investment, focus and energy might be helpful in unlocking the organisational value from huge investments in AI and creating high performance organisations, powered both by people and AI.

Let’s explore what might be going on in organisations from an AI and people perspective. 

Current Performance Landscape

One of the clearest goals for organisations using AI is to improve organisational performance. If we want to consider a high performance culture and environment we might have varying factors that would indicate the presence or absence of a high performance culture.

AI’s introduction into the workplace, has directly created the concept of workslop or AI slop. We are mostly now familiar with this concept of AI generated workslop or AI slop. For the purposes of this article we will use the definition from the original Harvard Business Review article that coined the concept. It is ‘AI generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task’ (HBR, Sept 2025). Or a more simple definition of this might be, work output that is below the standard required, so it is not considered high performance work. This perhaps provides a good proxy for the presence or absence of a high performance culture in an environment where AI is used.

So how prevalent is this in organisations? 2025 Global research from the University of Melbourne, indicates that 2 out every 3 employees report having relied on AI output without validating or checking the information. This backs up research from Stanford Media Labs (2026) that 53% of employees have received what they would consider workslop from their colleagues in the past month. This suggests that between a half and two thirds of employees in organisations using AI are either creating or receiving work that is considered below the standard required. This has several implications for high performance organisations.

Firstly, the producer of the work is not originating high performance work (at least some of the time). The second implication is that the receiver of the work now has to spend time and effort either revising the subpar work to a sufficiently acceptable level or completely redoing the work. Separate research from Betterup (2026) and Zapier (2026) puts the weekly effort by individuals to fix or redo this work at between two to three hours per week.

However, there is a third more insidious impact in organisations that is occurring.

The previous research published in HBR also showed that individuals who received workslop viewed the sender as less trustworthy, reliable and credible as a co-worker. Therefore, the extent to which AI is being used in organisations to create sub-standard work is resulting in a breakdown in organisational trust at both an individual and team level that is having a detrimental compounding effect on organisational performance culture in many companies.

What has happened?

2026 research from Betterup provides an appropriate framework in which to explore the context in which workslop, but lets call it what it is, sub standard work, has become a common occurrence in organisations using AI.

Betterup’s extensive research has shown that four main factors or conditions have a strong correlation with the presence or absence of workslop in organisations (and by extension the present or absence of a high performance culture in an organisation)

• How leaders in the organisations have communicated about AI. Strong people-centric messages strongly correlated with a lack of workslop
• Whether AI usage is mandated or encouraged. Mandated AI usage strongly correlated with the presence of workslop
• Employees trust the environment they work in. Lack of trust is strongly correlated with presence of workslop
• How much psychological ‘fuel’ people have. Employees having optimism and feeling a sense of agency and purpose about their role in the organisations is positively correlated with lack of workslop

So let’s explore some aspects of these in a little more detail to uncover what might be happening at the individual employee level in organisations. 

Leadership Communication around AI

Over the last couple of decades the language of engineering has been applied more and more to organisations and to people in them. 

Extensive research (Caesens, British Journal of Social Sociology, 2017),Taskin (2019) as well as early work by the sociologist Gareth Morgan in the 1990s, demonstrates that when leaders use engineering or mechanistic language to describe organisations and the people in them, this has a detrimental impact on employee job satisfaction, commitment and trust in the organisation. A 2025 HBR article ( Don't Let Tech Jargon Undermine Your Team's Trust) argued that by using jargon and in particular non-human or engineering language creates mistrust in the organisation Therefore, the language you as a leader use around AI sends a strong signal and message to your employees about what the organisation values. Let’s take two common terms as an example.

2026 Gartner research bemoans the fact that in their research only 22% of organisations are considered ‘AI First’ and that companies have work to do to be ‘AI First’ and is therefore from an external stakeholder perspective, an aspiration to aim for.

Deloitte research from 2026, Dealing with AI’s Cultural Debt, has a different perspective. In their research (looking at the challenges of AI in organisations), they pose a wonderful question for organisations. If you declare yourself as an ‘AI First’ company, what message and signal do you send to the people in your organisation? That they are second in line (at best?). The cynic in us may well believe you think that, but do you need to explicitly tell people they matter less than technology?

Another common term used by organisations is that they have a ‘human in the loop’. Again, instead of looking at this word through a workflow or engineering perspective look at it from an employee and a human perspective. Using terms like ‘ human in the loop’, sends the message that your employees are just another cog in the organisational machine. Intent here is important. If that is the message you intend to send to employees, that they are just another cog in the machine, then that is your choice as a leader. However, if this is not the intent, perhaps it might be time to rethink the leadership language you use around AI and people.

Added to this lack of trust and fear is further reinforced that your employees do not exist in a vacuum outside of the world. The external world is full of evangelists extolling a future world where we don’t have jobs, we don’t need money, where AI has replaced humans (and that is a good thing!). Is your leadership language reinforcing or dispelling that fear and mistrust?

Trust in the Organisation 

One could also make the argument that the way many organisations have introduced AI into the company has broken the trust of employees. 

Extensive research, Microsoft & Linkedin (2025), and Gallup/SHRM (2026), shows that the majority of companies ( 60%+) had no organisational wide plan or vision for rolling out AI into the organisation. And how this rapid introduction of AI into organisations, without any sense of how the organisation or indeed the employee might absorb it, has created a huge amount of mis-trust in organisations. A ‘move fast and break things’ mantra also applies to things that you might not want to break (and take a long time to repair), like organisational trust. This is backed up by Deloitte research from 2026 which shows that only 20% of employees have trust in their organisation and its intent around AI. This is not particularly surprising when you look at the example of how Meta tried to introduce (and had to roll back from) employee keyboard surveillance, or AI training as it was termed. What they perhaps mis-judged here is the limits of people being treated as second in line in organisations to technology.

Given that the single highest predictor of organisational performance is employee trust, (and this is borne out by extensive research over the last 20 years (Gallup surveys, HBR research, Google project Aristotle etc), you can easily see what might have happened to organisational performance as a result of this breakdown in trust.

Psychological Fuel

All of this combines to create what can be called the psychological fuel of the employee. This being the mindset that drives how motivated they are to do the job, how optimistic they feel about their role and their value to their organisations. And how much agency they feel they have over their role and their future. If I trust my company and my leader, if they signal through both behaviours and messages that I am valued in the organisation, then it makes sense that I am more likely to be motivated to not only do my job but do it to a high standard.

However, what many employees have seen and been told by organisations is a wholescale dialling back of the investment in people (as they are second class and must wait in line), while at the same time there is a full throttle investment in AI that has moved ahead of them in the hierarchy of needs in an organisation.

While it is always a bit of a lazy comparison to look at the 19th Luddites who with the advent of the spinning machines, actively broke the machines as they perceived it took away their jobs. Yet you can hear and see echoes of this in employee behaviour today, who are mandated to use AI tools, mistrust their organisations, told they are second in line to technology and fear for their future, how they might therefore engage in a passive-aggressive assault on organisations to create sub-standard work. Whereas the opposite might be the case. By creating the right environment and conditions for employees they could easily be using the technology to enable them to create much more superior work than they could by themselves.

So how might organisations rebalance this investment in both people and AI to ensure that the investment in both will create a more high performance workplace?

Rebalancing the investment

How much of the focus of your investment in your organisation has been in AI and the tools around AI and how much of the focus and energy of your organisation has been in the investment of people in the organisation to enable them to work effectively with AI? Has it been the 93/7% split that we have seen from research?

Early research (and it is of course early research) indicates that the organisations that are appropriately investing in people alongside an investment in AI will be the ones that will reap the rewards. Given the data points that we have explored in the article, this would seem like commonsense, and not exactly rocket science!

So what might that look like? At a high level this might simply be the investment in people through the hard work of leadership and management around people. And why?

At a minimum if it were to drastically reduce or eliminate workslop in your organisation, might this not be worth the investment. Once that occurs, then the path is open to creating superior work (the opposite of workslop) and a truly high performance culture and organisation, through motivated and committed use of AI by people who trust their organisation and trust the leadership of the organisation. Is this not the work of leadership?

Leadership Actions

Organisational and Leadership communication around AI

• External voices to your organisation are creating a narrative of fear and mistrust around AI. Spend appropriate strategic leadership time crafting your own organisational narrative around AI, that is not grounded in fear and based on restoring organisational trust through your employees. Like any other strategic communications program this will never hit 100% acceptance or buy-in. Change programs provide a ready made template for this ‘win the hearts and minds’ approach to creating and maintaining organisational trust.

Reposition People and AI 

• The current research strongly indicates that those organisations and people who are extracting value from People and AI are the ones who actively encourage and promote it but do not mandate it. Actively creating the organisational environment for growth and learning around AI as a tool and a technology.

Mandating use is similar to mandating training and development. People will attend but their mindset towards it will be negative. Shifting employee mindset is a key part of the narrative to move AI from creating workslop to creating superior work.

Invest in People Managers

• Decades of research and extensive longitudinal research from Gallup, show that 70% of the variance scores in employee engagement is directly linked to the manager of an employee. Employees want to hear the high level approach from leaders but want to understand how it affects them through their manager. Rebuilding organisational trust is directly linked to the manager’s capability to motivate, coach and provide meaning and context to employees. Investing in the capability of your managers and leaders to create the right conditions for both people and AI growth is vital if you want to create a high performance workplace in the age of AI. And to be clear, if you're thinking of completely replacing an employee’s direct manager or coach with AI, perhaps re-read the data above.

Replenish Employee’s Psychological Fuel.

• All of this investment by leaders in how they message the value and contribution of employees in an organisation and how managers, on a daily basis with their actions and behaviors reinforce this sense of value, contribution and purpose will go a long way to replenishing employee psychological fuel. When our battery is low, we need to dial back certain activities and functions. When the battery is full, we can perform and exceed all expectations.

Conclusion

This article focused on the question of whether by overdexing on AI in the last couple of years, some organisations have lost sight of the need and opportunity to focus on and invest in the people in your organisation.

There is a very old argument at play here which has re-surfaced as part of the narrative around AI, namely that the spending of dollars on technology is an investment and the spending of dollars on people is a cost. If you embrace this philosophy then of course your approach will be to replace the cost with the investment. The early research indicates that this is unlikely to be a winning organisational strategy.

The early evidence (backed up by years of previous research on technology and people) shows that a dual investment in both AI and people will be the way to build a high performance culture in your organisation. There is an opportunity here for organisations to significantly close the gap between the investment being put into AI and the return on that investment. The equation has perhaps one additional input, rebalancing your investment in people.

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