AI is particularly suited to back office operations in banks and financial institutions analysing large amounts of financial data. Typically banks and financial institutions employ large numbers of people to undertake functions such as compliance documentation, fraud review, transaction monitoring, credit analysis and financial reporting. AI systems designed by Palantir Technologies and SAS Institute for example, can review financial data and identify anomalies much faster than manual teams. The impact of AI on specific industry segments is summarised as follows -
Investment banking and capital markets
Analyst roles are vulnerable to AI systems. The business folklore of junior bankers working 100 hour weeks using Excel models, pitch books and risk management due diligence is already under severe pressure as these tasks are highly structured and can be executed by AI. Examples already known include Goldman Sachs and JPMorgan deploying AI for financial modelling, earnings analysis and report generation.
Equities market research has been transformed as AI can monitor thousands of stocks, synthesise earnings and generate initial research notes faster than any human team.
Asset management
Quantative analysis and factor modelling can be easily augmented by AI and is increasingly occuring already. This situation is leading to a changing and evolving role for quantitative analysts.
Portfolio reporting and client communication is increasingly being automated with AI at the commodity end.
Active investment funds management comes under further pressure as passive funds are now better guided by AI-driven strategies.
Compliance reporting which is a very large cost centre in financial markets is being substantially automated with AI. The use of automation was an existing trend for many years but AI enables a faster rate of uptake.
Retail and commercial banking
Loans underwriting is already largely algorithmic and automated for retail consumers and the SME business level already. AI does not alter the trend but merely further reduces the remaining human review layer.
Customer service and branch banking continues a long decline with face-to-face service reduction. This situation however is subject to fluctuations due to community pressure and increasing consumer preferences for personal interaction for specific services. AI's influence is limited in this line of business activity.
Fraud detection and ani-money laundering (AML) monitoring is already within the AI-dominated sphere. Human reviewers have been shifting to exception handling only.
Financial advice at the mass market level already has limited use of robo-advisers. This segment is however subject to regulation and government oversight and the requirement for financial advice licenses, accountability and legal liability. The use of robo-advisers beyond limited information provision and recommendations for the mass retail market has not yet occured. High-net individuals particularly prefer human advisers and personal banking managers rather than an automated service. Various financial advice scandals in the sector may also limit the use of AI for the time being.
As with all industries, the use of AI in finance and banking is most easily implemented in large data analysis, administrative and reporting tasks. It is not well suited to client relationships and regulatory, legal and compliance responsibilities.
Graphic arts and visual design are another industry that is heavily exposed to AI particularly with impacts such as hierarchical pyramid compression. Tasks and projects that once needed a team of junior artists can now be completed by a single art director using AI tools. AI image systems can now produce concept art, advertising visuals, books covers, storyboards and marketing graphics. Specific industry segments affected are discussed as follows -
Commercial illustration and stock art
Stock photography and illustration is already heavily impacted. Companies such as Shutterstock, Getty Images and Adobe all now offer AI image generation. The market for generic commercial illustration has largely collapsed for independent artists.
Illustrators who designed books covers, editorial art and advertising assets, mainly mid-tier commercial work, now face severe income compression. This blog uses AI generated images having once held accounts with commercial image suppliers such as Shutterstock.
Advertising and brand design
Mood boards, concept art and campaign mockups are increasingly AI-generated at the brief stage.
The jobs of junior designers whose purpose is to execute pixel-perfect images under senior creative direction are now heavily at risk as these tasks are automatable.
UI/UX design
AI tools: Such as Figma AI can automate layout generation, component creation and user flow suggestions. Junior UI designers who develop wirseframes face significant automation pressure.
UX research such as interviews, synthesis and insight generation remain more protected however even parts of these processes such as synthesis and pattern recognition can be managed through AI.
The multi-part series covering AI, published in this blog, has been researched and compiled using Claude ai (Anthropic), ChatGPT (OpenAI), and Grok (Xai).
In 1902, British explorer Robert Falcon Scott spotted a large group of large black and white birds at Ross Island, Antarctica. This was among the many milestones of Scott’s famous Discovery expedition: the first breeding colony of emperor penguins.
Now, only 124 years since this penguin colony was discovered, emperor penguins have officially been listed as endangered, along with the Antarctic fur seal. As the world warms, Antarctic krill are shifting southwards and sea ice is shrinking at record levels. And these unprecedented changes are having a domino effect on these species.
These are the first penguin and pinniped – marine mammals that have front and rear flippers – to be given this conservation status in the Southern Ocean. Their perilous situation is a critical turning point, and shows how rapidly the Antarctic environment is changing.
At the same time, the spread of highly contagious avian influenza, or bird flu, adds a new and immediate threat to Southern Ocean wildlife, compounding the pressures of climate change on stressed species.
Antarctic fur seal with pups at Sailsbury Plain on South Georgia. The number of fur seals has dropped by over 50% since 1999.Posnov/Getty
Dramatic declines linked to climate change
The first emperor penguin breeding colony was discovered at Cape Crozier, on Ross Island, during Robert Falcon Scott’s Discovery expedition in 1902. A decade later, Scott’s Terra Nova expedition returned, in part to collect emperor penguin eggs. It was an ill-fated expedition, immortalised in Apsley Cherry-Garrard’s famous book, The Worst Journey in the World.
In the 1960s, Scott’s son, Sir Peter Scott, one of the founders of modern conservation, helped establish the International Union for the Conservation of Nature’s Red List. Just 124 years after those early discoveries at Cape Crozier, that same framework has now been used to classify emperor penguins as endangered. The swift arc from discovery to extinction risk is a striking reminder of how quickly the species’ fortunes have changed.
Over nine years, between 2009 and 2018, emperor penguin numbers fell by 10%. Their numbers are expected to halve by 2073.
Southern elephant seals are now officially listed as vulnerable.Mary-Anne Lea, CC BY-ND
In just a decade, they have been reclassified on the IUCN’s Red List, going from of “least concern” – those species that are widespread and at low risk of extinction – to “endangered”. The IUCN’s red list is the comprehensive information source on the extinction risk status of species. This shows the remarkable speed at which these seals are declining.
Climate change and bird flu
Both of these dramatic declines are linked to climate change. Warming ocean temperatures and a reduction in sea ice affect the availability of the Antarctic fur seal’s key prey, Antarctic krill. Krill are shifting southwards and moving deeper, potentially making them less accessible to some predators. Competition with a growing population of whales has also increased.
Emperor penguins, by contrast, are completely dependent on sea ice. They use it as a stable platform for courtship, incubating their eggs and rearing chicks. But as sea ice declines and becomes less reliable, their breeding success is increasingly threatened. If the ice breaks up before chicks are fully developed, many are unable to survive.
At the same time, the spread of highly contagious bird flu adds a new and immediate threat to Southern Ocean wildlife. High mortality associated with avian influenza has also caused the uplisting of the southern elephant seal to “vulnerable” this week.
Some elephant seal populations have experienced more than 90% of pups dying, alongside sharp declines in breeding adults. These represent tens of thousands of animals lost, with many Antarctic fur seals also dying as a result of bird flu outbreaks.
Emperor penguin chicks at Cape Crozier.Mary-Anne Lea, CC BY-ND
We need to know more
Emperor penguins, Antarctic fur seals and southern elephant seals are three of the more widely researched Southern Ocean predators. But there is still a lot we don’t know, because of the remote location and the difficulty of sustaining research over time. And there are many species we know far less about. Antarctic ice seals, including Weddell seals, crabeater seals, leopard seals, and Ross seals, have “unknown” population trends on the IUCN red list, meaning there is not enough data to know if numbers are declining.
These recent listings make clear the urgent and ongoing need for improved, real-time monitoring. We need to know much more about wildlife health and population trends, the Antarctic environment and sea ice quality.
Human-driven threats facing Antarctic wildlife are many, and cumulative. To respond, we need to better protect Antarctic habitat and the species that live there. We need to reduce the interaction of marine species with industrial fishing. And we must improve how we assess current and suspected threats in Antarctica, when there is growing evidence of impacts.
Defining these animals as endangered is a stark reminder of how quickly Antarctica is changing before our eyes. Without a rapid reduction in greenhouse gas emissions and sustained conservation action, these species may be lost forever.
The impact of AI is the most pronounced in the film and television industry with a variety of occupations impacted by the technology. The WGA and SAG-AFTRA union strikes in the United States in 2023 highlighted the concerns of people employed in the creative industries. Breaking down the various subsectors in the film and television industry, the role of AI can be easily defined -
CGI and VFX production
AI now covers environmental generation, crowd simulation, rotoscoping, motion cleanup, texture creation, background characters.
Rotoscoping, cleanup and compositing are traditionally large pools of junior labour and these tasks are being automated rapidly. Mid-tier VFX companies are under existential pressure with work bifurcating toward very high-end boutique work but the commodity work is fully AI generated. The roles that are disappearing are junior asset builders, repetitive compositing roles and the large teams that produce background elements.
AI tools are Unreal Engine, Blender, Runway, Sora and similar programs.
Acting and performance
AI can and is already producing synthetic actors to create digital doubles and AI-generated crowds.
Background artists are already displaced due to AI generated crowds and extras in a limited manner. This displacement of extras, crowd performers and minor background roles is expected to increase.
Voice acting is severely threatened as synthetic voices are increasingly now near indistinguishable from real human voices and can be used for minor characters, video games, commericals and dubbing. Studios can licence a voice and use it indefinately.
AI tools are Nvidia and Runway AI
Writing
AI can already operate to develop plot structure, dialogue drafts, storyboarding, episode outlines, alternate scene ideas. Writers room teams that once had 6-12 junior writers now only require a headwriter, 2-3 senior writers and AI-assisted drafting tools. A showrunner with AI-assistance may need only 2-3 senior writers rather than a full room.
Localisation and dubbing is already occuring using AI replacing human translators and lip sync dubbing artists at scale.
The reality is that with time and patience, AI will enable very small teams to produce cinema-quality films. Early versions of AI films can already be found on YouTube however many of these projects suffer from continuity failures and many technical deficiencies in storytelling structure.
The safest roles in the AI-era are those positions with creative authority, not basic production. Examples could be roles such as showrunner, art director, creative director, lead animator, production designer. These are decision-making roles and decide what should exist rather than merely producing it.
As artificial intelligence (AI) continues to be developed and implemented in various forms across workplaces, the exact impact for employment is becoming apparent even in this early stage of adoption. When discussing AI, it's important and extremely relevant to define the capabilities of AI.
AI carries out three activities across all industries -
automates the repetitive layer
compresses the workforce pyramid
raises the value of senior decision-makers (to an extent)
An example only to demonstrate this impact is the organisational structure in industry.
An industry that once had this structure -
1 Director
3 Senior professionals
15 junior staff
Under AI capability becomes a structure with -
1 Director
3 Senior professionals
3-5 AI-assisted operators
AI across many white collar industries removes what is called the "first draft economy''. Many jobs existed primarily to produce first drafts of various outputs such as reports, media releases, policy notes, research documents, scripts, designs, code for information technology. AI can now produce much of this instantaneously.
AI is starting to hollow-out the traditional 'career ladder'. The junior roles that people once used to enter professions are disappearing first. This situation does have long term consequences for how expertise and experience is developed in society. This creates a "pipeline problem" and is becoming one of the largest and dominant structural challenges of implementing AI.
AI does compress some organisational hierarchies and enables an increase in the number of people or functions that a single leader can manage. This is known as the 'span of control' which AI increases while reducing certain managemernt layers in organisations. Hierarchical compression is only one aspect of the AI's impact but equally the very shape of organisations also changes with -
fewer administrative workers
fewer reporting layers
smaller teams with higher productivity
leaders responsible for larger spans of activity
Roles that involve accountability, legal responsibility or political authority will remain human dominated. AI does reduce the documentation workforce that produces reports, compiles data, drafts documents and summarises information. It does not replace roles that have decision authority, physical presence, strategic judgement and/or legal accountability.
As another example of structural change, before AI implementation, a very large organisation often had this structure -
Executive leadership
Senior managers
Middle managers
Supervisors/team leaders
Large operational workforce
After AI implementation, the organisation could be structured as -
Executive leadership
Senior specialists
Fewer managers
AI-enabled reduced operational staff
Effectively the middle and bottom tiers shrink.
The multi-part series covering AI, published in this blog, has been researched and compiled using Claude ai (Anthropic), ChatGPT (OpenAI), and Grok (Xai). Later posts on this topic will list specific industries where change is already happening.
Coffee first entered human lives and veins over 600 years ago.
Now we consume an average of almost two kilos per person each year – sometimes with very specific preferences about blends and preparation methods. How much you drink is influenced by genes acting on your brain’s reward system and caffeine metabolism.
Coffee can raise your blood pressure in the short term, especially if you don’t usually drink it or if you already have high blood pressure.
But this doesn’t mean you need to cut out coffee if you have high blood pressure or are concerned about your heart health. Moderation is key.
So how does coffee affect your blood pressure? And if yours is high, how much is OK to drink?
What is high blood pressure?
Blood pressure is the force blood exerts on artery walls when your heart pumps. It’s measured by two numbers:
the first and biggest number is systolic blood pressure, which is the force generated when your heart contracts and pushes blood out around your body
the lower number, diastolic blood pressure, is the force when your heart relaxes and fills back up with blood.
Normal blood pressure is defined as systolic blood pressure of less than 120 millimeters of mercury (mm Hg) and diastolic blood pressure of less than 80 mm Hg.
Once your numbers consistently reach 140/90 or more, blood pressure is considered high. This is also called hypertension.
Knowing your blood pressure numbers is important because hypertension doesn’t have any symptoms. When it goes untreated, or isn’t well-controlled, your risk of heart attacks and strokes increases, and existing kidney and heart disease worsens.
About 31% of adults have hypertension with half unaware they have it. Of those taking medication for hypertension, about 47% don’t have it well-controlled.
How does coffee affect blood pressure?
Caffeine in coffee is a muscle stimulant that increases the heart rate in some people. This can potentially contribute to an irregular heartbeat, known as arrhythmia.
Caffeine also stimulates adrenal glands to release adrenaline. This makes your heart beat faster and your blood vessels to constrict, which increases blood pressure.
Blood caffeine levels peak between 30 minutes and two hours after a cup of coffee. Caffeine’s half-life is 3–6 hours, meaning blood levels will reduce by about half during this time.
The range is due to age (kids have smaller, less mature livers so can’t metabolise it as fast), genetics (people can be fast or slow metabolisers) and whether you usually drink it (regular consumers clear it faster).
The impact of caffeine on blood pressure from coffee (and cola, energy drinks and chocolate) varies. Research reviews report increases in systolic blood pressure of 3–15 and a diastolic blood pressure increase of 4–13 after consumption.
The effect of caffeine also depends on a person’s usual blood pressure. An increase in blood pressure may be more risky if you have hypertension and existing heart or liver disease, so it’s best to discuss your coffee consumption with your doctor.
Phytochemicals that directly affect blood pressure include melanoidins, which regulate the body’s fluid volume and activity of enzymes that help control blood pressure.
In a review of 13 studies that included 315,000 people, researchers examined associations between coffee intake and the risk of hypertension.
During study follow-up periods, 64,650 people developed hypertension, with the researchers concluding coffee drinking was not associated with an increased risk of developing the condition.
Even when they examined data by gender, amount of coffee, decaffeinated versus caffeinated, smoking or years of follow-up, coffee was still not associated with an increased risk of developing hypertension.
The only exceptions suggesting lower risk were for five studies from the United States and seven low-quality studies, meaning those results should be interpreted with caution.
A separate Japanese study followed more than 18,000 adults aged 40–79 years for 18.9 years. This included about 1,800 people who had very high blood pressure (grade 2-3 hypertension), with systolic blood pressure of 160 or above or diastolic blood pressure of 100 or above.
Here, risk of dying from cardiovascular disease, including heart attack or stroke, was double among those drinking two or more cups of coffee a day compared to non-drinkers.
There were no associations with death from cardiovascular disease for those who had either normal blood pressure or mild (grade 1) hypertension (systolic blood pressure 140–159 or diastolic blood pressure 90–99).
The bottom line
There is no need to give up coffee. Here’s what to do instead:
consider all factors that influence your blood pressure and health – family history, diet, salt and physical activity – so you can make informed decisions about what you consume and how much you move
be aware of how caffeine affects you and avoid it before having your blood pressure measured
avoid caffeine in the afternoon so it doesn’t affect your sleep
aim to moderate your coffee intake by drinking four cups or less a day or switching to decaf
if you have systolic blood pressure of 160 or above or diastolic blood pressure of 100 or above, consider limiting to one cup a day, and talk to you doctor.
Microplastics have been found throughout the world's oceans and at all levels of the water column following a comprehensive survey of over 1,885 sites across the planet. The survey conducted by researchers from Japan, China, New Zealand, Italy, the Netherlands and the United States located microplastics across depths in the ocean including the deepest parts. The Mariana Trench, for example, recorded more than 13,000 microplastic particles per cubic metre nearly 7 miles down.
Of particular concern from the findings, is that the smallest particles were distributed almost evenly throughout the water currents, rather than being more at the surface level than at the bottom of the ocean. Another key finding from the survey measurements is that the polymers in these plastics were accounting for very strong reading of the carbon in the water. At depths of 2,000 metres, the polymers comprise as much as 5 per cent of the carbon.
These high carbon levels may reduce the capacity of oceans to aborb carbon dioxide from the atmosphere and thus enable global warming.
