Is AI in Business, the Future?

Authored Feburary 2024

Find out how AI can create efficiencies in your business today

Since the dawn of time humans have invented tools to make tasks easier and save our energy for more creative pursuits. Now, artificial intelligence (AI) is not only freeing us up from tasks like driving, keeping shopping lists (hey Alexa!) or even painting award winning artworks, it is reshaping everything from disease diagnosis to the way we work.

For businesses, AI has the potential to be transformational: it

can generate rich insights by processing enormous quantities of data, automate complex or repetitive tasks, support strategic decision making and enhance competitiveness. It frees people to do what they humans do best: innovate, undertake revenue-generating activities and create imaginative solutions.

But every revolution in human history has been tinged with

fear – and AI is no different. Decision makers’ limited understanding has led to fear of investing in an opaque

technology with hard-to-quantify outcomes. Many people also fear being replaced by machines and relegated to a career in robot polishing. How can these fears be overcome, allowing businesses use AI to create strategic advantage and

transform their business, while they prepare their workforce for the future?

• Buyer behavior models can provide deeper insights into the customer journey, allowing sales processes to be improved and marketing to be optimised through more effective campaigns. Predictions based on new trends can help to build customer acquisition models and reduce attrition rates.
• Applying AI to customer relationship management (CRM) systems replaces intensive manual updates into a self-updating, auto-correcting system.
• Customer segmentation activities can be improved by creating tailored marketing programs, matching products and services with demand, highlighting hidden relationships and dependencies and foreseeing customer behaviors.
• Cyber threats and fraud can be predicted and losses prevented by targeting threats and vulnerabilities before they occur.
• In finance, predictive analytics models can forecast financial performance, evaluate investment risks and optimise financial portfolios.
• Risk assessment applications can predict the impact of decisions such as whether an acquisition or operational change will be profitable
• In healthcare, applications are being used to optimise expenditure and deliver better treatments by mining huge volumes of data to predict health outcomes and identify relationships between diagnosis, medical treatments, risk factors and patient outcomes.

Bringing AI to the C-Suite

Despite the obvious advantages, Dr Richard George, Chief Data Scientist at Faethm AI, says that machine learning for business applications has been difficult to implement.

“AI and ML provide a lot of untapped potential for businesses although tools have not yet made it to C Suite decision-making.

“When you don’t understand what machine learning can do for your business, how data is managed or manipulated, or you can’t verify the accuracy of the models being used, it can be difficult to justify investing in the technology,” he says.

He advises teams considering whether a machine learning application is right for their business to begin by rating the importance of the decision they’re trying to make.

“For an autonomous car, you want 100 percent accuracy when it comes to predictions about pedestrian or animal movements that could cause collisions. For sales, a model that is 90 percent accurate is probably acceptable.”

Models that are now coming into ML applications for business are at a point of accuracy that meets business needs, he says. Models are available to support strategic decisions such whether to enter a new market or predict the success of an acquisition. In HR, tools like faethm are being used in decision support, including predicting how planned innovations will impact jobs.

Making AI’s impact on the workforce positive

There is no doubt that some employees are at risk of losing their jobs as machine learning becomes more advanced. This particularly impacts staff who may not have a strong educational background and staff in female dominated areas such as retail workers, bookkeepers and receptionists.

Some jobs, such as those held by people working in call centres, have actually been augmented by early stage natural language processing, which has replaced monotonous calls and made their work more interesting, Dr George says.

“They are now able to focus on case calls and create bespoke solutions to meet specific needs.”

For other businesses, however, they need to think about how they can start educating or retraining staff to move into knowledge-based work. After all, it makes business sense to retain staff who have a high level of corporate knowledge and longstanding commitment to their employer, particularly in the midst off workforce shortages.

In 2021 Woolworths allocated $50 million over three years to its Future of Work Fund to help upskill, reskill and redeploy more than 60,000 team members impacted by industry disruption and technological change.

The company is providing training in digital, data analytics, machine learning and robotics, with further investment planned for advanced customer service skills, team leadership and agile ways of working.

Dr George says that one of the biggest challenges to AI-led workforce transformation is that the business function that identifies cost-saving automation solution is separate to the L&D function.

“People whose roles are impacted are identified at the start, but often thinking about training doesn’t occur until the end.”

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