AI-driven technology: Workplace efficiency or an agent for disruption?
Scott Dodds, Ultima CEO
In today's rapidly evolving business landscape, the impact of AI-driven technology such as ChatGPT, on workplace dynamics cannot be ignored. But is it a gift or a curse to individual thought? And does it really help with productivity or at some stage, will it take over the need for human contribution, collaboration and problem solving?
As a C-level executive, it is crucial to critically evaluate the role of AI and determine whether it brings about workplace efficiency and scalability – or simply acts as an agent for disruption. Furthermore, if it is deemed to be a disruptor, how do you find ways to use it to your advantage?
Let’s explore the topic and find out how to get AI onside.
The obvious advantages
→ Scalability and adaptability
Alongside efficiency, AI offers the ability to improve scalability and adaptability. From customer service chatbots to intelligent data analysis, AI empowers businesses to handle increasing volumes of data, customer enquiries, and complex tasks with ease. A good example here would be in the e-commerce industry, where AI-driven recommendation engines analyse customer preferences and behaviour to provide personalised product suggestions – scaling customer engagement and improving sales.
→ Enhanced decision-making
Another obvious advantage of AI that is perhaps most pertinent to corporate leaders is enhanced decision-making. Who would not welcome better business analytics and predictive modelling or valuable insights for informed decision-making? By analysing vast amounts of data, AI can uncover patterns, trends, and correlations that may not be readily apparent to human analysts. This empowers us to make data-driven, strategic decisions for our organisations.
→ Workplace efficiency
AI has the potential to revolutionise workplace efficiency by automating repetitive tasks and streamlining day to day processes.
By leveraging machine learning algorithms, businesses can also achieve higher levels of accuracy, speed and productivity in various operational areas. A notable example would be in the manufacturing industry, for instance, where AI-powered robots automate repetitive assembly line tasks, leading to increased production speed and accuracy.
It all sounds great doesn't it? So, what's the catch?
Demystifying the perceived problems
Much of the way we think about AI is shrouded with negativity – mostly related to the disruption it may cause. And of course, there’s the most natural and immediate reaction, which is always: Will it replace me at work? However, I believe it’s up to us to look at the situation from a positive point of view, rather than through a negative lens, so let’s demystify some of the common perceived problems:
Disruption in job roles
While AI enhances workplace efficiency, it can definitely disrupt traditional job roles –but this doesn’t have to be a bad thing. Yes, automation may replace certain repetitive tasks, leading to concerns about job displacement. However, I believe that business decision-makers must proactively address these challenges by reskilling employees and identifying new roles that align with the evolving technological landscape.
Let’s not forget that once upon a time, in the advent of agricultural machinery, many farmers feared that their roles would become redundant. What really happened is that the machinery only made them more efficient – and enabled them to be more productive in other areas.
A modern-day example can be found in the healthcare industry, where AI-driven diagnostic tools are assisting doctors in analysing medical images, reducing the time taken for accurate diagnosis – and allowing healthcare professionals to focus on treatment planning and patient care. This kind of disruption can be good, if we work with technology, not against it.
Microsoft’s use of the word ‘Copilot’ for their AI services is deliberate and accurate. The AI enhancements to their suite of software products are designed to support huge efficiency and optimisation for their human counterparts not to replace them.
Modern aircraft have for many years been able to handle take-off, flight paths and landings using software/AI alone, but would you feel happy flying in a plane with no human backup? I know I wouldn’t be comfortable yet. There is no doubt that many roles will be disrupted or changed but this is the natural outcome of progress. How many jobs that were around when I started in the tech industry in the 80s are around today? Not many, and yet the market for technology skills continues to grow exponentially.
AI raises ethical concerns surrounding data privacy, bias and transparency. C-level executives therefore need to ensure that AI-driven technologies align with their business’ ethical standards and are developed and implemented responsibly.
Building trust and transparency in AI systems is crucial for long-term success. A good example can be seen in social media platforms, which employ AI algorithms to detect and remove inappropriate content, ensuring user safety and adherence to community guidelines.
Replacing human interaction
Rather than viewing AI as a replacement for human workers, we need to see it as having the power to augment human capabilities – allowing employees to focus on complex problem-solving, creativity, and critical thinking.
Take the customer service industry, for instance, where AI-powered chatbots handle routine customer enquiries, freeing up human agents to address complex customer issues, resulting in improved service quality and efficiency.
Early adopters could gain a head start in the market, improving customer experiences and decision-making capabilities.
C-level executives must carefully evaluate AI's potential impact on their industry and explore strategic implementation opportunities.
Does anything really take the place of human interaction? I don’t think so; people buy from people.
But that’s why business leaders must carefully evaluate AI's potential impact on their industry and explore strategic implementation opportunities. In the retail industry, AI-powered demand forecasting models do a great job of analysing historical sales data, market trends and external factors to optimise inventory management – minimising stockouts and maximising profitability.
The fear factor
Business decision-makers can play a pivotal role in addressing concerns by fostering a culture of learning, providing clear communication, and demonstrating the benefits of AI implementation in improving employee experiences and driving business growth.
In other words, it’s up to us to put a positive spin on AI.
By staying updated with emerging AI trends, monitoring industry developments and fostering an agile mindset, businesses can maximise the benefits of AI-driven technology while mitigating potential disruptions. However, AI is not a product.
We learnt several years ago in the early days of Robotic Process Automation (RPA) that to get to the full benefits of automation the software is the easiest part. The difficulty is understanding your organisations processes and the way humans interact with the plethora of corporate systems.
It becomes a cultural and to some extent political challenge to manage change in any organisation at scale. This will be exactly the same for AI. Any change will be a cultural discussion from the top of the organisation down. To really understand the potential benefits and potential risks of AI is a C-level challenge, not just a CIO challenge. Everyone will have to be aware of the impact and the changes required to thrive in the AI age.
As AI Large Language Models (LLMs) excel at replicating writing styles on demand, there is a risk of criminals using LLMs to write convincing phishing emails, including emails in multiple languages. This may aid attackers with high technical capabilities but who lack linguistic skills, by helping them to create convincing phishing emails (or conduct social engineering) in the native language of their targets.
For more complex tasks, it's currently easier for an expert to create the malware from scratch, rather than having to spend time correcting what the LLM has produced. Therefore, the risks of smarter social engineering attacks will increase exponentially, which will demand that organisations are constantly alerted to the latest threats through evergreen training and awareness. At Ultima our services include social engineering risk assessments and learning systems through our AntiSocial Engineer division.
Conclusion: AI needs HI (Human Intelligence)
AI-driven technology has the potential to bring about substantial workplace efficiency and scalability but disruption in mindset, management and cultural challenges need to be considered in its implementation.
My conclusion? AI is most effective when combined with HI (Human Intelligence). Business leaders must carefully assess their organisation's needs, understand the potential benefits and risks of AI, and develop a strategic approach to effectively leverage its capabilities. At Ultima, we have the expertise to help you do all of that – and more.