Is AI in Business, the future?

Is artificial intelligence in business the future?

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.?

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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 humans do best: innovate, undertake revenue-generating activities and create imaginative solutions.

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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?

What is AI?

Generally speaking, artificial intelligence refers to any cognitive process exhibited by a non-human entity.?It’s an umbrella term that covers neural networks, deep learning, machine learning, computer vision and natural language processing.

AI exists to solve problems that require repeated, complex manual effort, and solve problems beyond human capacity by efficiently extracting insights from immense data sources that continue to grow over time.

There are three types of AI:

·????????Narrow AI is created to solve a specific problem and is already widely used. For example, by looking at a user’s preferences, a program is able to determine their likes and dislikes and make recommendations, providing a more personalised experience to the user. Narrow AI with natural language processing capabilities is used to provide customer support and for spam filtering. In marketing, the technology is used for digital ad placement, ad targeting during the customer journey, streamlining sales processes and enhancing the accuracy of sales forecasts.

·????????General AI simulates the behaviour of the human brain, and can undertake cognitive tasks such as processing, contextual understanding, learning, generalising and creating original solutions. Commonly used call centre applications use models of natural language processing that can read text, listen to conversations, interpret and respond appropriately using a bank of results. However, advanced models use deep learning to search prior conversations, blogs and news items from across the internet and to create a unique solution, rather than drawing on preloaded responses.

·????????Artificial Super Intelligence is currently only a theory and exceeds human intelligence in every way. It will use AI’s to learn from itself, at exponentially increasing levels of intelligence, also known as the ‘Intelligence Explosion’. It is the type of AI that has given rise to fears of super-intelligent AI going rogue and wiping out humans. Fortunately this is only currently an issue in sci fi books and films.

Why should businesses adopt AI?

“While it has been talked about for decades, the AI revolution is now underway. The technology will massively disrupt business, and if businesses fail to join the revolution they risk becoming uncompetitive,” says Doug Ross, Senior Partner and Managing Director from Adaptovate.

“The technology is still evolving rapidly, but AI can already help businesses to improve access to data in crucial business areas, including customer relationship management, enterprise resource management, fraud detection, finance, human resources and IT.”

How does machine learning and business intelligence benefit business?

Business intelligence, artificial or otherwise, is all about data. Accurate, real-time data provides granular insights into how a business is performing, helps decision makers to understand trends?better and respond to a rapidly changing business environment to achieve competitive advantage.??

But while business intelligence uses basic calculations to provide answers, machine learning (ML) supercharges business intelligence. ML applications use predictive and cognitive analytics to identify trends and patterns from complex data sets and mathematical models to make predictions beyond the scope of human analysis.

Marketing is a leader in the application of business intelligence models augmented by machine learning tools – tools like Google Analytics, which has led to more effective advertising budget usage through targeted ad placement, realistic sales predictions and better planning.

ML applications are empowering business across a wide range of sectors, supporting faster decision making, increased productivity and operational quality and allowing proactive responses to predicted challenges – reducing costs associated with playing catch-up.

·????????Buyer behaviour 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 behaviours.

·????????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.

Machine learning tools freely available on the internet, but to get the most out of them each business needs a bespoke solution. Competitive advantage comes from the data you use, how those tools are applied and the business problem you apply them to.

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.”

“Companies will reap the benefits of supporting staff motivated to transition to new types of roles.”

To support staff to transition in an evolving business, employers need to:

·????????ask staff to look at the skills they have

·????????undertake an assessment of the types of training they need to form part of the business’s future

·????????either provide that training internally or work with an external provider to give staff the skills they need

Using AI to underpin competitive advantage through leadership

For businesses that are still unsure about taking the plunge into AI, Chairman of Siemens Jim Snabe says that in a time of upheaval like now, the future is unpredictable and this presents big opportunities, he says.

“Leadership is your biggest competitive advantage. We are lucky to be leaders in time of dramatic change.

“We want to [use AI to] take care of the details that matter the most, then let human creativity unfold.”

This article is also published online at adaptovate.com/en-au/

Get in touch with our Regional Growth Partners to find out how ADAPTOVATE can help you get the competative advantage in your business. Specialising in implementing new ways of working at scale.

Australia: David Gumley

Singapore: Cindy Gan

North America: Megan Burke

Europe: Nick Forde