Why AI needs EQ: our take on the future.

January 21, 2022

Contrary to popular belief, AI isn’t a new technology. In the 1950’s, Alan Turing began to explore the mathematical possibility of whether machines could use the same reason, logic and calculations that a human uses to solve problems. For Turing - and those who came after him in the decades that followed, progress was slow.


The advancement of AI is heavily dependent on the computing power available. It wasn’t until the early ’90s that the processing power of computers was finally capable of enabling AI and ML research and adoption on a mass scale. Even as this became possible, the same fundamental question applied: can machines mimic human intellect?

Fast forward to the 21st century and Artificial Intelligence as we understand the term is the ability for computers, or computer-controlled robots, to carry out tasks or solve problems as a human might. It’s percolated into our daily lives via the apps and websites we use most regularly. In fact, you carry it around in your pocket all day on your smartphone. The upshot of this technology? Superior consumer experiences. Quicker response times. Better product matching. Hyper-personalisation.

But how does this technology actually work?

In this article, you’ll learn:

  • The key differences between AI, ML, NLP and RPA.
  • How and why the AI industry is growing at such an impressive rate.
  • Why we think it’s important at Forward and why it’s a key investment area here.
  • Why we believe the magic truly happens when you combine artificial intelligence with human intelligence.

What is AI? ML? NLP? RPA?

Artificial Intelligence. Machine Learning. Natural Language Processing. Robotic Process Automation. Let’s break them down and talk about how they fit together.

Artificial Intelligence (AI) is technology that enables a machine to simulate human behaviour. It’s able to scan vast amounts of data, iteratively process that data and combine it with smart algorithms to spot defining features, patterns or trends in the data set. When you use facial recognition to unlock your iPhone, or you type in a destination to Google Maps or Waze, this is powered by artificial intelligence.

Machine Learning (ML) is a subset of AI which allows a machine to automatically learn from past data without programming specifically, to improve the outputs over time. Think about every time your email provider warns you that an email could be harmful, ML is processing millions of data points across millions of emails to make recommendations on which could be malicious.

Natural Language Processing (NLP) is a technology that enables machines to understand written and spoken language. Caught up with Siri or Alexa recently? NLP is the technology behind both of those products.

Robotic Process Automation (RPA): is a digital worker which can complete one or all steps in a process otherwise completed by a human. It’s used in specific processes which are labour intensive, repetitive and often quite boring for the employee to carry out manually. If you’ve ever conversed with a digital customer service assistant via chat on-site and then been handed over to a member of their customer service team, you’ve experienced RPA in action.

So enough with the acronyms, just how popular is this technology today?

The AI landscape in 2022.

According to Tech Round, the UK AI startup ecosystem has grown over 600% in the past 10 years, with the sector bringing in £2.41 billion worth of investment in 2020 alone.

This technology has provided endless new opportunities, enabling businesses to solve complex problems across a range of industries, at scale. Increased efficiencies, productivity and improved accuracy rates deliver impressive savings on the bottom line. Hyper-targeted marketing campaigns and faster, interactive, self-serve customer service drive revenue on the top. In McKinsey’s Global State of AI 2021 report, they state “AI adoption is continuing its steady rise: 56 percent of all respondents report AI adoption in at least one function, up from 50 percent in 2020.” These numbers are increasing most in emerging economies such as China, the Middle East and North Africa.

In 2021 we saw some monumental raises for leading AI and data focused businesses. Revenue intelligence platform Gong, raised $250 million in Series E funding in 2021 on a $7.25B valuation. UiPath, one of the global leaders in AI-powered RPA went public in one of the biggest ever US software IPOs raising £1.3bn. Databricks, a data warehousing and machine learning specialist, raised $1.6 Billion Series H investment at $38bn valuation.

Gartner predicts the AI software market will reach $62B in 2022. And it’s showing no sign of slowing down.

Why does Forward invest in applied AI?

Our investment team at Forward have been on the lookout for outstanding applied AI companies for a while now. As a sector, it’s booming. A survey conducted by CognitionX found that London has twice as many AI companies as Paris and Berlin combined. We believe you can summarise the potential of AI into three key points.

It’s industry agnostic.

From healthcare and infrastructure to agriculture and legal, AI is already transforming a range of industries at an impressive pace. At Forward, we’re seeing founders tackling big, complex problems in industries that have often lagged behind in technological innovation. Many are plagued with unstructured and siloed data, admin heavy processes and teams performing monotonous tasks that could be alleviated by AI.

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Customers are demanding more.

Gen Z is now the largest population cohort globally, with an estimated 2.5 billion people. This generation is digitally native, mobile-first and hot on convenience. They expect tailored recommendations, real-time accurate data and slick customer service, preferably without making a phone call. This hyper-connected generation is driving a shift in services, marketing, product development and customer service, powered by technology like AI, to help the rest of us keep up.

Its ability to scale.

AI’s capability goes far beyond a human’s physical ability. The technology is trained on huge datasets, that would be impossible for one or even a team of humans to process at the same speed. But what does this processing power look like in practice? One example is how AI has enabled scientists to solve previously impossible problems, like correlating a patient’s genome and dozens of other biological variables with the drugs likeliest to cure their cancer.

Keeping humans in the loop.

AI has huge benefits and growth potential. At Forward, we believe that the real magic happens when combined with the human characteristics that a machine can’t simulate: emotional intelligence, sophisticated reasoning, creativity and imagination.

Though AI excels at spotting trends in data, it can be exceptionally difficult to get right. Luke Smith, Partner and Lead Investor at Forward says, “applying AI to problems with a limited margin for error is very hard to do, particularly in industries where the errors have high stakes like healthcare or legal. In some instances, you are dealing with scenarios where the answers have to be 100% correct, with many factors at play. Human intervention is required to oversee the outputs from the machine and also needed to relay any particularly sensitive information back to the customer. While there is great progress being made in automating back-office tasks with AI and Robotic Processing Automation, customer-facing interactions based on insights from artificial intelligence is a long way off from being completely automated.”

The mental health and wellness space is a great example of where artificial intelligence and human intelligence work collaboratively. Entrepreneurs are developing products to help solve problems like loneliness and mental health problems through AI-powered helplines or diagnostic tools which capture the key information it needs to effectively match the user with a suitable therapist or medical professional. Megha Prakash, an investor at Forward goes on to explain, “we’re also seeing AI used in collaboration with the IoT, to help monitor and improve the quality of living for elderly or incapacitated individuals. The wearable or smart tech in their homes tracks thousands of data points each day, which AI can then analyse to assess if there are any major changes in the person’s daily behaviour that could be a cause for concern. A relevant individual like a healthcare professional or family member can then be alerted.” The research in this field is compelling and a great example of how AI findings can be used to form the next action to be taken by a human.

Now is the time for mass adoption of AI.

In 1997 a key breakthrough in the development of AI was the downfall of Garry Kasparov. The former world chess champion who lost to IBM’s supercomputer, Deep Blue. Many saw it as proof that artificial intelligence was catching up to human intelligence, whilst we know today that’s not entirely true, today’s applications of AI are solving some extremely complex problems.

  • British Pharmatech company Exscientia originated the world’s first 3 AI-designed drugs into Phase 1 human testing and IPO’d on the NASDAQ on 1 October 2021 at a >$3B valuation.
  • UK National Grid ESO halves error of electricity demand forecast using transformers since May 2021. Lowering carbon emissions and costs as they aim for net-zero generation by 2025.
  • Moorfields Eye Hospital and NHS have developed a computer vision system that can automatically detect and monitor age-related macular degeneration (AMD). Which is the most common cause of blindness Europe and North America, hard to detect initially with no known cure.

In our portfolio, we’re seeing bold entrepreneurs tackling problems that have been historically very hard to solve.

  • Robin AI, the legal-tech business that has built a unique contract management service, which combines software, machine learning and world-class legal professionals.

  • Sourcery, an AI code assistant that helps developers write better code faster, clean their code, reduce technical debt, and instantly refactor. Trusted by over 7000 developers at household brands like Sky, Microsoft, Amazon, and LinkedIn.

  • Juno: which brings together legal expertise with software and AI to offer conveyancing that’s clear, convenient and reliable. Juno’s goal is to become the UK’s largest and most trusted property law firm.

Building the future, together.

Artificial Intelligence in all its forms is here to stay. It’s growing. Across sectors and across geographies. It’s solving problems humans couldn’t have imagined 50 years ago. It’s keeping up with the evolving requirements of the next generation of consumers. It’s smashing fundraising records. And it’s becoming more mainstream as each month passes.

It started as a quest for machines to mimic human intellect. At Forward, we believe that you need both types of intellect. Particularly when solving sensitive, human problems.

As an employee or as a consumer, AI will become embedded even more in our daily lives. And at Forward, we can’t wait to see what this technology can do next.

Got big ideas?

If you’re an early-stage founder with a big idea in AI, we’d love to hear from you. You can get in touch via our Offices Hours Programme here.

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January 21, 2022