Artificial intelligence (AI) is everywhere. But its current form is far from Hollywood movie fodder. It hasn’t hit Minority Report levels of insight and it’s not about to gain world domination.
In fact, current AI technology is much more mundane. But you don’t have to wait for it to reach its full maturity: here are some very practical ways to implement it in your organisation right now.
Key AI terms
First, it’s worth debunking some of the common terms surrounding AI. Often, it is tagged onto solutions and packages as a marketing ploy. To choose the right tools you need to be able to separate the wheat from the chaff.
Current AI in the workplace is limited to one or two functions such as voice recognition or natural language processing. A lot of today’s solutions use machine learning, which is a subset of AI.
Machine learning: This is where a computer is ‘trained’ on certain types of data - images for example - and then get very good at recognising similar data and patterns, such as image recognition. There’s a feedback loop that helps the computer improve, so it understands when it’s right and wrong. This can be applied to many different business problems depending on the data the AI is trained with.
Voice assistants Siri, Alexa and Cortana all use machine learning. Apple’s Animojis use machine learning that is specialised in facial tracking, which is a novel use at the moment, but with a lot of potential applications across law enforcement and the business world.
Deep learning: This is closer to our vision of true AI as it is based on the way the human brain works. It uses a neural network to gain insights and make decisions, just like how your brain has collections of neurons specialising in different areas. Google has used deep learning to reduce its error rate on speech recognition in its devices. Microsoft recently used it to translate spoken English into written Mandarin in real-time.
Current uses of AI
We’ve briefly touched on some examples of AI in action today. However, it has a much wider reach than just speech or image recognition. PayPal uses machine learning to detect fraud and the legal sector uses it to read documents. There are uses for AI in every sector, from HR and marketing to logistics and healthcare.
With so much on offer, where do you even start? Broadly speaking, AI can help in three ways:
Helping with daily tasks: This is where it helps with mundane, time-consuming and repetitive tasks. It frees up your time so you can focus on higher-level strategic and creative work.
For example, x.ai will schedule meetings for you and Less.Mail helps you manage your inbox. There’s others that can read and categorise CVs for a busy HR department, optimise a marketing campaign and highlight contracts for a legal team.
Speech control: We’ve become used to seeing Google Home and Amazon Echo in our living rooms. Soon they’ll be springing up in our workplaces. Alexa for Business is a voice assistant specifically designed for enterprise clients. It can schedule meeting rooms, arrange a calendar and answer questions.
Data security: Thanks to a spate of high profile data breaches (Costa Coffee, Premier Inn and Timehop are the most recent in a long list) the public is focused on data protection. The stakes are high because of the General Data Protection Regulation (GDPR), which has fines of up to €20 million or 4% of global revenue for breaches. Now, companies are using machine learning to protect against spam, phishing attacks and malware.
AI can also detect and keep security systems up-to-date with new threats. Additionally, it can understand what ‘normal’ behaviour looks like and flag any abnormal behaviour, like an employee downloading sensitive information to a USB.
With a great many uses across organisations, it’s little surprise that almost 60% of decision-makers state that they are using or trialling AI in their organisations. The same respondents expect 29% of their current applications will be enhanced through the technology.
Get your goals right
It can be tempting to try every single AI tool on the market. But that’s a waste of time and resources. You need to narrow your potential applications down. The starting point for this is to understand what challenges your business is facing. Work out what business problems you want to solve. This will help you set goals for your AI projects. From this, you can consider the available technology and whether these align with your goals and challenges.
Also consider your investment in AI. Some tools, like email assistants, are relatively cheap to implement but can make a huge difference to your employees’ working lives. Schedulers and AI virtual assistants can be good to trial first as they also introduce your employees to the technology.
These kinds of ‘quick win’ projects are critical to gaining widespread buy-in across your organisation. Prove AI’s value early-on and you will be able to trial more innovative, larger AI initiatives later on.
You may also have to change your organisation’s culture. Employees will need training on how to use AI and what it means for their roles. Some might be concerned that it will take their jobs, when actually it is likely to claim less jobs than originally feared. But all roles are likely to evolve, notably through automation of mundane daily tasks, allowing employees to focus more on strategic and creative work.
Communication is key to your AI initiative’s success. Both inside and outside your organisation. Any value you’ve achieved through use of the technology needs to be shouted far and wide.
Many people don’t realise that they already use AI. Google searches use it to improve results, and it’s something we use every day. But 54% of employees believe they don’t use it in their personal lives. It’s important to highlight to people that we all use AI and the many benefits it brings to our lives.
Experiment now, benefit now
AI is still in its infancy but you should still experiment with some of its early applications. By using the technology in small ways now you can get your organisation ready for larger uses of AI later-on. Plus, there’s the potential productivity, security and efficiency improvements.
Remember to align any AI use with your wider business goals and don’t be tempted to use it just for the sake of it. Instead, consider how current tools can help you now and prioritise the right tech that will give you the largest returns for the least investment.
Photo by Katya Austin on Unsplash.