I started out as a Tech but as I’ve progressed I’ve had to take on more and more man and project management to the point that it feels like I spend more time helping people than fixing broke computers.
One of the more confusing but essential parts of project management, especially within large corporations, is handling the budget. It can be deeply satisfying to make everything line up, but it is just as often frustrating when external influences stop things from matching expectations.
First, budgets are frequently demanded long before it is reasonable to produce them, particularly in cloud or integration work. Senior stakeholders often want to know how much something will cost well before anyone can estimate it with any accuracy. Most technical or delivery teams would prefer to complete a proof of concept before providing numbers, but that rarely happens. Instead, an initial figure is asked for, and once it appears on a PowerPoint slide it becomes accepted as absolute truth.
This behavior leads to the familiar cycle of pushback. Delivery teams will initially include a large margin of error, only for that number to be negotiated down to something stakeholders find more palatable, often without context or awareness of what actually needs to be delivered. The result is that early estimates are wildly inaccurate. Any attempts to explain this are often smoothed over, quietly edited out, or ignored altogether. As a project manager, you must keep putting the caveats back in or formally record your objections whenever this happens.
Second, budgets change. Prices change. Currencies fluctuate. Even something as small as the licence type for a single piece of software can alter the long-term cost of a project by hundreds of thousands of pounds. A good project manager should set aside time each month to review the budget in detail and flag any major shifts. Many of these will not be explicitly reported, so you will need to chase people down. Costs have a habit of changing for the strangest reasons, with new items quietly added or adjusted without explanation.
Make it part of your discipline to check what has changed each month, identify the impacts, and estimate the longer-term effects. But be careful not to overdramatise this. If you constantly ping stakeholders saying “the budget has increased again”, they will soon tune out. There is an art to deciding when to escalate and when to wait for a more suitable opportunity.
Third, watch out for simple mistakes. Everyone makes them, and every organisation has its quirks. As a contractor or new joiner, you are more likely to miss these. Check your figures with long-term staff who know the local systems. Even experienced people can be caught out by a change in a subsidiary process or reporting rule.
Common problems include currency errors. If your reporting is in dollars but your billing is in pounds, exchange rates can cause nasty surprises. Find out whether the company has a fixed corporate exchange rate and use it. Sometimes people even report values in their local currency without realising that the invoices are in another. It happens most often between dollars and pounds or euros, and it can either blow your budget or save you money, depending on direction.
Finally, beware of unexpected success. This particularly applies to Cloud or AI-based services. When something works brilliantly, people will naturally use it more. Usage means cost, and you can quickly find that enthusiastic adoption pushes you into a higher billing tier or usage zone. Always keep an eye on growth patterns, because success can quietly double your costs overnight.
Framing is a political tool, and we probably should not use it in IT, but everybody does.
Essentially, framing means using particular terms to promote a viewpoint or a way of seeing something. It happens all the time, and it is a perfectly normal part of communication. For a fuller explanation, I would recommend reading “Don’t Think of an Elephant: Know Your Values and Frame the Debate” by George Lakoff, which provides useful background on the subject.
You see framing frequently in corporate IT, but you can fight back against it.
When framing is being used against you, particularly when you are trying to get something done, you will often hear complex technical language or reassuring, almost fatherly terms misused. You might hear phrases such as “advisory board” for a group that is supposedly just there to help. But in reality, it may be a group of gatekeepers trying to ensure that nobody does anything they do not like.
You can challenge this by flipping the framing around.
For example, if there is an approval document, which is itself a positive and authoritative term, you can simply call it paperwork.
“We are nearly ready. We just need to complete the paperwork.”
This diminishes what another part of the corporation might describe as an advisory document, governance document or strategic approval document.
The ultimate version of this, which has also been used in American politics, is the phrase “permission slip”.
Suppose you are waiting for approval from a governance board inside a corporation, and it calls its document a “strategic approval document”, which makes it sound like something grand and unarguable when it might be nothing of the sort, but if you refer to it as a permission slip, you completely change the frame.
It stops sounding like guidance, responsible oversight and strategic governance. Instead, it becomes paperwork handed out to a child by someone in authority.
I do not advise doing this. It is not a particularly nice tactic, but you will see people use it against you. They will use overly grand phrases to justify their own work, while using diminutive words and phrases to describe yours.
This will undoubtedly be the flavour of the month across the internet, particularly on platforms such as LinkedIn. People will suddenly be saying, “Aha! AI isn’t saving the world. CEOs are seeing the cost of all that token usage and realising that they shouldn’t have replaced people.”
Yes, some CEOs will be receiving unexpectedly large bills, but there is nothing new about the underlying problem. It is the same challenge every corporation faces when assessing value for money and trying to understand the total cost of a decision before committing to it.
My favourite recurring example is the comparison between contractors and permanent employees. Taken as a whole, a good contractor does not cost more than a permanent employee, provided you pay a sane market rate and you get what you asked for delivery-wise. Permanent employees come with many additional and often less visible costs, including benefits, training, leave and potential employment liabilities.
This does not mean that one option is automatically better than the other. It simply means that avoiding consultants or contractors does not always produce the savings an organisation expects. A good consultant who delivers genuine value is as good a deal as a dedicated employee. {This is a shameless plug}.
The same principle has appeared throughout the history of business outsourcing. It may look inexpensive to outsource work to the cheapest available supplier in another country, but is it really cheaper if the result is increasing technical debt and creating remediation costs further down the line?
Going back even further, buying cheap tools may appear to be a cost-saving exercise. However, if they need to be replaced repeatedly, they may ultimately cost far more than buying the right tools in the first place.
AI is no different. Every generation falls for some version of the same promise. When something appears too good to be true, it usually is. Everything has a cost, and there is no such thing as a free lunch.
What we need to avoid now is another knee jerk reaction. AI is brilliant and is a major step up in what corporations do day to day. However, it is not a universal solution, and its costs go beyond simply doing the work and providing the necessary computing power.
Vast amounts of investment have been poured into AI companies, and those investors will eventually expect a return. One way or another, that is likely to mean that prices will rise and costs will increase.
So, we return to the same advice that finance departments have been giving organisations since time immemorial: look at the complete cost of a decision.
Do not ask only how much something will cost this year. Ask what it could cost over the next ten years. Consider the supporting systems, the people, the remediation work, the supplier risks and the potential cost of changing direction later.
Before making large-scale changes, take the time to understand what you are buying, what it will replace and how much the service is likely to cost over its entire lifetime.
As a deeply technical person, I have always slightly resented PowerPoint. It can feel like communication with extra steps, or like turning everything into a very basic “See Spot run” version of the world. That said, I am aware that, from a manager’s point of view, when they have so much information thrown across their desk, something neatly laid out and clear can make their job much easier.
However, I have recently been lucky enough to work with someone with significant accessibility needs, and I am now seeing PowerPoint in an even grimmer light.
Often, other forms of communication are asked to be converted into a PowerPoint slide for the sake of presentation, even when the email containing the original data is perfectly readable by everybody. Yet the expectation remains that it has to be fancied up before adult humans are considered capable of coping with it.
This has always struck me as slightly annoying and needless work, but it had never really occurred to me how much of a non-inclusive pain it can be for people with accessibility issues.
A lot of the templates people use for PowerPoint, particularly those from larger vendors, are designed with sheer beauty in mind. They are often created by professional designers, and they can look brilliant. But they can also be an absolute devil to edit if you are not fully able-bodied and a wizard with a mouse. They are often far more like works of art than practical means of communication.
I do appreciate how good a polished PowerPoint slide can look, and I do appreciate the clarity they can sometimes bring. But are they always necessary? Do we need to produce a beautiful slide rather than one that is merely clear, easy to edit, and suitable for communication?
So next time you are adding complex background images and hundreds of little dots to make a Gantt chart, have a think about how someone who only has voice commands would edit it.
I am currently sitting in that little used reception area that every giant corporate building seems to have for guests who are waiting for someone to come down and collect them. You know the sort of place: odd potted plants, huge chairs, and the sense that it has been designed to be used as little as possible.
The reason I am sitting here at the start of my working day is that I left my pass for this client on my desk at home because I am an idiot.
While sitting here, I assumed I could simply go to security, explain who I was, identify myself, get a temporary pass printed, and head upstairs to work. However, I was wrong. Those days no longer exist.
Autonomy by individuals, particularly in well-established service roles or roles seen as replaceable, has become massively limited, and it has become noticeably worse over time. Gone are the days when security guards would really know you. I normally know most of the security guards, cleaning staff, and the other support people who appear in the office at the same time as I do, which is usually about 6:30 in the morning. But they are all kept in very rigid boxes, because that makes them easy to replace with no impact on the smooth running of the building facilities.
And here is the nub of it: that also makes them easy to replace with non-humans.
I think this is one of the core and genuine worries about AI. Yes, there will always be things that require a human touch, and there will be things that robots have not yet mastered. But by allowing work to become so regimented, with such fixed boundaries around its deliverables and such an absence of adaptability, we have set ourselves up to be easily replaceable by AI and similar systems.
So if your job has very strict boundaries, very strict deliverables, and does not reward innovation or adaptability, then I think you are in the area of humanity that should be most worried about being replaced. That does not matter whether you are in the service industry, deeply technical, or anything else. If you cannot display humanity or any of its advantages during your working day, and if your work is bounded by strict borders with easily quantifiable inputs and outputs, then you are at real risk.
Historically, that risk meant being replaced by a cheaper human. I suspect that, eventually, it will mean being replaced by a cheaper non-human.
Let us step back and talk about General Electric, some 30 years ago, when the first major rounds of outsourcing were being done and call centre outsourcing was brand new. I started in a call centre doing help desk and support work, in an 800-person call centre in the middle of Leeds, Yorkshire. They were just beginning the first stages of outsourcing to India.
There was joking, of course, and there were practical issues. Postcodes were new to the country taking on the work, and they had to be explained. Training had to be done. Processes had to be documented. All that kind of thing, but it was still happening, and as a freshly hired person, I was worried that this was the beginning of the end when I had only just started, but a very clever person told me something that came back to me recently. Whether you can be replaced by another person, a piece of software, AI, or anything else comes down to a few simple things.
Can your work be wrapped in strict definitions?
Is it easy to encompass and define precisely?
When you do your job, do you simply deliver the average expected result?
That average delivery might not even be fully within your control. If there are exact SLAs to deliver against, and your job is simply to meet them, then you may already be in trouble. If the answer to these questions is yes, then you are at serious risk of being outsourced. Back then, that meant outsourcing to India. Today, it can mean outsourcing to AI, automation, or any number of other things.
So, how do we prevent it? Perhaps we do not. Perhaps the real answer is that we have to work with it.
Back then, I was told to make sure I was better than everybody else. Be value for money. Because regardless of what any company might say, value for money always matters. If you come in, do what you consider an ordinary day’s work, and nothing more, then you are at direct risk from AI. AI is, by definition, an average of what it has learned. If it uses the company’s internal data, it becomes the average of what that company has historically been able to do.
So if you are doing an average job, or even just a consistently good job within a tightly defined structure, you are at strong risk of being outsourced by something that can improve on average delivery. It can improve on cost, dependency, repeatability, and consistency.
The second question is whether your job is easily defined. The stricter and clearer the definition of what you actually do, the easier it is for AI to replace you. With traditional outsourcing, work had to be defined well enough for another person or team to take it on, but there would always be variance based on human understanding and interpretation. With AI, the better the definition, the easier the replacement becomes.
So now we know whether we can be replaced. The next question is how we adapt to the companies using AI to put that into practice.
I think the answer has to be defined at an individual level, rather than by industry or even job title. I strongly suspect that AI, just like outsourcing to cheaper countries, will eventually be able to do a large amount of non-physical, interaction-based, white-collar work. We are not going to win by pretending that will not happen. The Luddites did not stop progress by burning down machinery, and we will not stop this by simply objecting to it. Progress will march on.
So how do we deal with it?
We deal with it by using the default that AI provides as a stepping stone to become exceptional.
That is going to be hard in a number of areas, particularly where there is wholesale outsourcing or where there are hard definitions of what is absolutely correct. Copy editors are having a very difficult time at the moment, because their job is to make something complete and correct. If AI can do that, it is hard to go over and above to prove your value.
But for work that involves any form of soft skill, from customer service to facilities, management, consultancy, or technical delivery, we are going to have to produce better than average. That does not mean giving every hour of your life to various corporations. It means recognising that they will be able to supply the average through AI. You will have to remove the base part of the work and focus your effort on what AI produces, then improve it, shape it, and add value beyond it.
The main difference between historical outsourcing and AI outsourcing is the turnaround cycle. It is also about whether your improvements are learnt and absorbed by the AI.
For example, if your work was outsourced to another country, the comparison was whether you were better at the job than the outsourced team. As you learned and improved, you might have been able to stay ahead. They might have improved too, but there was still a human and organisational delay.
With AI, it may only be able to produce the best average result that all the data in your company can support. But it will constantly play catch up with you. That means you will have to keep re-referencing the baseline it produces. No longer will the question simply be, “Am I the best in the market?” The question will become, “Am I a meaningful percentage better than what the AI is already producing?”
That change will be particularly relevant to white-collar workers. I think they are especially vulnerable to this form of AI learning. But, ultimately, AI is here. The people with power see it as a way of producing better value for money with more consistency.
TLDR;
You are most at risk if you are an average worker doing an average day’s work, or if you are a white-collar worker whose output is easily defined and judged as either correct or incorrect. If there is softness in your delivery, use it. If your work requires judgement, adaptability, empathy, creativity, or context, keep developing those things.
Keep ahead of AI by using it as a starting point, rather than competing with it directly.
