Artificial intelligence (AI) should be used only when organisations have a specific use case for the systems or risk wasting time and investment, says customised software company Entelect solutions architect Rishal Hurbans.
AI – technically called narrow AI, as opposed to general and super AI – is becoming more prominent within businesses as greater computing power and data have made it feasible to experiment with AI to make money and uncover business opportunities.
“Owing to advances in technology, organisations can use data and advanced algorithms, as well as cheaper, more powerful computing hardware to achieve new and extraordinary things, like auto- matically describing images for the blind and detecting fraud in banking,” he highlights.
AI works well for optimisation and automation. If there is a digital process that can be optimised, then AI is suitable. The key is that AI should be fit for purpose and must add value to the business, freeing up staff time and helping the business meet its goals.
Specifically, companies can take a bottom-up or a top-down approach. With a bottom-up approach, businesses should identify a problem and then decide if using AI can solve the problem.
However, if a business does not have a use case for AI, but still wants to experiment with the technology, it can take a top-down approach, which adopts the concept of design thinking. If the business wants to use AI during the project, it must understand what data it has, consolidate it, analyse it and find trends that will inform their action plan, thereby learning about potential AI foundations and applications.
Businesses must experiment, as it is the only way to grow skills and knowledge in the industry and develop robust use cases.
As the need for new applications of AI grows, businesses will need to address the ethical issues regarding job replacement because AI adds business value and can help organisations to be better and more innovative, he avers.
However, AI will also spawn entirely new industries that will require skills that do not yet exist – much like what the Internet did for the search engine optimisation industry and what the industrial revolution did for machine artisans.
“Since we do not yet fully understand the capabilities of AI, we don’t understand the potential either,” notes Hurbans.
Therefore, AI will create more responsibility for those in leadership positions because they will need to ensure that the impacts are managed and well communicated.