The age of Artificial Intelligence (AI) has arrived. It’s here now, and it’s here to shape our future — for better or for worse. But with all the talk surrounding AI, it’s tempting to see it as a be-all-and-end-all.
Yes, AI is promising. But it’s not magic. Like all other types of technology that preceded it, AI needs a human touch to be truly beneficial. In fact, one of the key roles that we, as humans, should take on is to first evaluate if AI is truly the solution we’re looking for. For instance, if you needed to hammer a nail you probably wouldn’t pick a spanner. You might be able to get the job done, but it’s definitely not the best tool for the job.
AI, RPA, or DPA?
For any business undergoing a digital transformation, AI is usually regarded as the acme. The miracle solution. But the truth is, not every business or every automation project requires AI. In some cases, Robotic Process Automation (RPA) or Digital Process Automation (DPA) may be more relevant. The three are often mistaken for each other, but are actually different.
Artificial Intelligence (AI) is the use of data to train machines to develop human-like intelligence. For instance, in one of our projects with a logistics company, we were able to use our highly-intuitive ABEJA annotation tool on collected video data and Deep Learning models to train the machine to identify the objects being packed, as well as to count the total number of objects packed. This allowed the company to know whether customers’ orders were being fulfilled correctly. Generally speaking, AI is used to automate smart decisions that are informed by data — this involves human-like decision making capabilities by learning from available data.
Robotic Process Automation (RPA) is the use of software to automate repetitive, rule-based tasks. For instance, RPA can be used in a logistics company to maintain inventory levels. A software can be programmed to monitor the inventory numbers of a product, and to automatically place an order whenever it falls below a specified amount. Generally speaking, RPA is used to mimic simple human actions accurately.
Digital Process Automation (DPA) is the use of software to digitise, optimise, and automate processes across multiple business units. For instance, DPA can be used to automate the entire process of completing a customer order — from warehouse shelves to a packed box ready to be shipped. DPA often involves breaking down silos to look at both the front-end process and the back-end systems of any operation to design a better workflow.
Simply put, AI is about data, RPA is about tasks, and DPA is about processes. The three are intertwined, and often compatible — they all help to reduce operation costs, minimise human error, and allow employees to focus on high-value work.
Ultimately, we must rely on human intelligence to decide which technology works best for the use case, and to bring them together wherever appropriate. To get a closer look at the collaboration and discussions that occur before any technical project, learn how ABEJA worked with a client to implement a successful PoC project.
Why human intelligence is crucial for your digital transformation
Technologies such as AI, RPA, and DPA drive efficiency. But true digital transformation goes far beyond adopting a new technology, even if it’s chosen with care. In fact, the word ‘transformation’ already implies that this will be a major change. One that requires the entire business to adopt the right mindset, culture, and thinking processes.
A common mistake that most business leaders make is to try to use automation to boost their company’s public image or to measure its effectiveness against a single goal, such as to reduce manpower costs. Unfortunately, this often leads to a narrow focus on specific tasks or outcomes — one that does not contribute to a better overall customer journey. The result is often duplicated systems, money wasted, and no tangible outcomes.
To avoid mistakes like these, business leaders must think bigger. Instead of focusing on a single step, look at the entire process with a customer-first perspective. Rather than think about improving public perception, consider improving the whole company by ensuring organisational alignment across silos. Even if you’re intending to start with a small PoC project, you’ll need first to get a holistic understanding. Because it’s only by seeing the big picture that you’ll understand how to enhance the little details.
A more structured way to do this is to employ the design thinking methodology. This is a 5-stage process to empathise, define, ideate, prototype, and test — one that we have used with success for every ABEJA project. Design thinking is why ABEJA Singapore’s machine learning experts insist on taking the time and effort to understand our client’s business from start-to-end. That’s stage one, empathy. At stage two, we’ll conduct a thorough audit of their processes to define the problem. Then, we’ll ideate by identifying all the potential areas where technology can provide value. This is followed by prototyping and testing, which are the stages where we plan and implement PoC projects.
Design thinking methodology enriches the business aspect, while the collaborative and incremental approach of the agile methodology enhances the development aspect. This is especially important for large-scale projects such as a digital transformation that involves an entire company.
The fact is, from design thinking to agile development, all of these are — and must be — powered by humans. So even though the age of AI has arrived, human intelligence is here to stay.
Is your company planning a digital transformation? Start it right with a conversation with ABEJA Singapore (Global) to find out how we can help your organisation combine both artificial and human intelligence for success.