Which organisations are best positioned to benefit from the A.I. insurgence?

 In today's fast-paced business world, leveraging artificial intelligence (A.I.) can be the key to gaining a competitive advantage. With the ability to process vast amounts of data and perform complex tasks quickly and accurately, A.I. is rapidly transforming the way we work.

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The questions from employers: is the technology really capable of improving efficiency and productivity in such a way that boosts revenue? If suitable technology exists, how does a business position themselves to seize this opportunity?

 

What do we already know?

 

A.I. refers to the ability of machines to simulate human intelligence and perform tasks that typically require human problem-solving or decision-making. These software systems can be programmed to analyse vast amounts of data, identify patterns and trends, and make predictions based on that data. Within the A.I. umbrella, Machine Learning is a subset of AI that enables technology to learn and improve their performance without being explicitly programmed to do so.​

 

The obvious risk: Can you actually trust it?

One concern that businesses would have when introducing A.I. into their processes is the reliability of the technology and the potential liability for mistakes. While A.I. systems can perform tasks more quickly and accurately than humans, they are not infallible and can make mistakes. A.I. is no different to most other software; the responsibility for any mistakes ultimately falls on the organisation implementing the technology.

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Can the technology live up to the hype?

"Yes, but...".

 

If there are systematic flaws embedded into the design of the software or its' implementation, A.I. could still produce sub-optimal outcomes. Any business contemplating A.I. software must consider whether the vendor has a wide enough understanding of the data landscape; not just in its' chosen field, but can it deliver outcomes specific to the client's operating environment. Most software would likely need a robust implementation and 'bedding in' period before it delivers optimum outcomes and A.I. is no different. A prospective customer would be wise to understand the ongoing Machine Learning capability of the software and the development roadmap of the vendor.

 

For many businesses it will be a question of Efficiency versus Risk. What are the expected gains brought about by implementation of A.I.? Conversely, what can be quantified of the known risk? Which party(s) is liable for flaws in the software, it's implementation or it's ongoing use? Do the efficiencies and improvements being gained, outweigh that risk?

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Capitalise on the opportunity.

 

Make no mistake, A.I. is a competitive advantage. Successful implementation will free up valuable human resource. The improved efficiencies in a business could be the difference between success or failure.

 

Most Kiwi businesses will want a gentle rate of adoption, likely making their first foray into A.I. and Machine Learning in a small facet of their operation. Where will businesses aim first? Recurring process that are slow, prone to error and can be easily measured both in terms of risk and improved efficiency. Overall, a strategic approach should should include the following steps:

 

1. Identify opportunities: The first step is to identify areas where A.I. can be most beneficial to the business. This may involve analysing existing processes and identifying areas that are time-consuming, repetitive, or prone to error.

2. Choose the right technology: There are a wide variety of A.I. technologies available, each with its own strengths and weaknesses. Businesses should carefully evaluate their options and choose the technology that best fits their needs, budget and aligns with their risk appetite.

3. Monitor and adjust: Once the A.I. system is in place, it's important to monitor its performance and adjust as necessary to ensure it's meeting the organization's goals. This may involve tweaking algorithms, adjusting configurations, or providing additional training to personnel.

 

Conclusion.

 

Overall, while there are risks associated with the introduction of AI in business, these risks can be managed through careful planning, monitoring, and risk mitigation strategies. Adopting new technology is second nature in much of our lives, but A.I. represents a jump that most businesses won't be comfortable with from Day One. A strategy that enables businesses to start small and then ramp up is likely to sit well with most decision makers.

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Further thoughts.

 

Payroll Intelligence believes the era of Machine Learning and A.I. has arrived for payroll.

We are a specialist firm that combines technology and consultancy, for the purpose of assessing endemic payroll errors. Our job is to help clients who have already made mistakes. Unfortunately, these mistakes exist in most Kiwi businesses, one way or another.

 

We believe we can get out in front of these mistakes and stop them before they happen. It requires a higher standard of payroll technology and an evolved reconsideration on whether humans are better deployed elsewhere.​ If Tempus Payroll or our Arrears Assessment services are of interest to you, we would be happy to hear from you.