AI will innovate your SME, but get to grips with it first
7 min read
14 March 2019
For too long Artificial Intelligence or (AI), has been seen as the great yet scary unknown for businesses. The possibilities of AI, and it's potential to upscale and innovate your business are endless. But ensure you do your homework first. Let my easy-to-read guide on AI for SMEs be your first positive step towards AI learning and implementation.
How to make AI work for your business is one of the most pressing questions facing companies worldwide. It’s also an unavoidable question, with those failing to consider it at risk of being left behind and compromising their competitive edge.
AI is amazing but do your research first
While it’s been talked about for years, the practical applications of AI for businesses are slowly being realised and it’s not a decision for organisations to leap into headfirst.
Don’t believe in the hype either; while AI adoption is certainly heating up, corporate adoption is still lagging behind, giving organisations the time and space to experiment and pilot AI.
AI can inform business strategy, revolutionise customer service and improve recruitment and retention, but with so much noise surrounding AI at the moment, it’s difficult to know what to invest in and what to avoid…
The time to invest in AI is now
For decades, AI has played the role of the villain in Hollywood blockbusters. A far cry from the handy virtual assistants most of us keep in our kitchens.
Just as AI has integrated seamlessly into our daily lives, it’s doing so in business too. We’re already seeing AI playing a role in customer experience, process automation and predictive analysis.
AI can solve a lot of workplace stress
AI can help all sizes of businesses with labourious and often stressful tasks such as data processing and completing manual tasks. In fact, it’s estimated manufacturing and sales and marketing will account for over two-thirds of AI business opportunities.
However, a desire to be seen at the cutting edge of technology doesn’t necessarily correlate with intelligent business strategy.
It will be the organisations able to harness AI to achieve their long-term business goals, without getting caught up in the hype, who will reap the rewards.
How can you best use AI technology?
Does it make more sense to build technologies from the ground up, or purchase third-party infrastructure as and when you need it? The likelihood is a hybrid of the two.
Building AI infrastructure allows businesses to customise technology to your exact needs. Compared with investing in pre-packaged solutions, it allows for flexibility to modify key functionality when you need to.
The general standpoint in the industry seems to be that, unless you’re a dedicated AI product company, if the product already exists, buy it and invest time and money in aligning your business strategy to maximise its potential.
Use AI to get ahead of the competition
Just like in cybersecurity, the sector is experiencing a skills-gap due to the time it takes to train and recruit AI specialists. However, as the skills gap closes and the application of it in business becomes the status quo, the future is looking bright.
Making a smart investment Research shows 84% of businesses agree using AI platforms to solve burning issues will see them race ahead of the competition, but it’s important to understand it’s a marathon, not a sprint.
Just like most investments, simply throwing money at AI won’t create business value. No single technology will transform your business overnight.
Research and experimentation are key
AI is only worth investing in if it serves a purpose for your business. Which processes can AI streamline or make more efficient? Which tasks can AI automate, freeing up staff to spend more time on other more important things?
Applications like Artificial Neural Networks and Machine Learning can save time and money across departments including but not limited to sales, finance, recruitment, legal and marketing.
Building over buying AI systems has its positives and negatives
Success will come with learning from mistakes and ironing out hiccups to make platforms and applications as efficient as possible. A good example is how AI is being used in the banking industry which is infamous for time-consuming administration.
When it comes to identifying fraudulent activity and transactions, machine learning technologies can detect unusual behaviour to prevent accounts from being compromised, giving customers a greater sense of security and reducing the arduous task of manually reviewing requests.
The evolution of AI as we know it is built on complex maths
It’s revolutionised the way companies operate and will continue to do so, but not at the rapid rate we’ve experienced in the past decade.
While we’re still at the beginning of the AI journey, much of the critical groundwork has already been laid. Future advancements will be a result of continued machine learning and deep learning, plus problem-solving.
AI means positive news for smaller businesses
Because they can focus on refining AI platforms rather than having to rip-up and replace every few years. One of the biggest barriers to AI development is the amount of data needed to fuel deep learning.
Researchers are working on ways to fast-track deep learning using smaller amounts of data. If possible, this will unlock the potential of AI to assist in a wider scope of tasks.
The AI fear is simply paranoia – look at the positives
The biggest fear with AI is that it will replace human employees and automate jobs. However, the opposite is true; AI has the capacity to empower every employee to achieve more with less but, as the saying goes, you have to be in it to win it.