The term digital transformation is a great buzz word for media attention, but what does it actually mean when we peel back the hype and unpack the concept for those caught in the ‘digital divide’.
Even more so in the last few years since the COVID-19 pandemic swept across the globe, digital technologies have transformed the way we live and work. There is no doubt about it, we are living through the fourth industrial revolution. There is often a slight unrest as new technologies enter the market, challenging the status quo and disrupting traditional business models. Some of these technologies fall by the wayside as they jockey for position in a highly competitive market, whereas other technologies become ubiquitous and form a narrative that is so deeply embedded in society that we sometimes may not realise. If you don’t believe me – just Google it, or alternately we can jump on a Zoom to discuss.
The clear value of technology is in the information we can now capture thanks to the advances in technologies. With the application of these technologies to solve complex business challenges, we now have access to a world of information sources via the “internet of things” (IoT). The internet of things is a network of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors, and connectivity tools to enable these objects to collect and exchange data.
There is a lot of value in “big data” – you just need to know what you’re looking at. That’s where the field of data science was born. Data science is a discipline that includes finding ways to collect, process, and analyse data to make it useful. The ability to analyse large, complex data sets and extract business intelligence is a specialist skill that informs “data-driven” decision making.
As we learn new ways to extract, augment, and transform data into useable insights, new technologies have emerged to help speed up the process, and continuously improve the performance of the growing technology ecosystem. The rise in artificial intelligence has provided a way that organisations can become more “agile” and adapt to a rapidly changing marketplace, however it can become confusing to differentiate the jargon without being completely immersed in it, so for brevity’s sake the following distinction can be made – artificial intelligence, machine learning and data science are all terms used to describe various methods of using computers to process and analyse data.
Data science is a field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data to make better decisions. Artificial intelligence is a computer system that can do things that normally require human intelligence, such as understanding natural language and recognizing objects. From this, machine learning defines a way of achieving artificial intelligence by giving these computers the ability to learn from data without being explicitly programmed.
Now that we’ve tried to decouple those terms, quite frankly why would you care? Well, it’s not just enterprise scale organisations that benefit from these technologies. The same technologies evolve to become embedded and contextualised into our daily lives. As a small business owner, it’s likely you wear many different hats on any given day, and perhaps are a lifelong learner, picking up the requisite skills and tools along the way to adapt to the changing economic landscape.
But did you know that artificial intelligence is closer to hand and easier to use than you may think? This broad categorisation of technology is implemented in many common business applications that may apply to your industry or niche, such as:
- Automation of deployment and monitoring of business applications
- 24/7 customer service via chatbots and intelligent virtual assistants
- Text to speech tools that can understand and generate natural language
- Data tagging, classification and labelling based on trained data models
- Recognition of images, voice patterns and pattern sequences in data sets
- Continuous integration and continuous delivery (CI/CD) of solutions
- Realtime insights and object detection for processes and systems
The way in which artificial intelligence and machine learning can be used is only limited by our imagination – and is front of mind for the leading technology companies globally including Microsoft, Google, Apple, and Facebook.
The adoption of new and emerging technologies does not always have to reach saturation point before you can look at applying it to help whatever challenge you may be facing – there is a strong community both online and locally who are passionate about helping us all navigate through these turbulent times.
Find your way to a meetup event, hackathon or accelerator program, or just reach out to me on LinkedIn and I’ll connect you with your nearest cohort of entrepreneurial types!