AI and the Enterprise

Artificial Intelligence has caused a storm in the world as new versions of this technology have come online from various tech giants. What does this mean for the modern enterprise?

This article will attempt to unpack some of the implications of this technology and what modern managers can expect to see in the near future. Artificial Intelligence refers to the transfer of tasks normally undertaken by humans (and requiring intelligence) to machines and predominantly computers. It requires the assembly of data, comparison of that data, and often the drawing of conclusions that may inform decisions or even making choices without human intervention. Many have expressed concerns about the loss of jobs and the potential for human extinction at the extreme.

There are various flavors of AI, ranging from super-specialized narrow applications that do only one thing extremely well to broad-based "general" applications that consume vast amounts of data and address almost every query or task. In between are the Voice Assistants, Virtual Assistants, and other "bots." The use cases typically involve prompts to the AI followed by responses that reflect the understanding of the challenge. In the background is "Big Data," whereby digital data is mined for relevance and assembled into a task or response.

It almost goes without saying that the internet has facilitated the age of AI by sucking up humankind’s collective experiences and creating logical links between these data points. This is very similar to the rise of Enterprise Resource Planning Tools that seek to capture every aspect of a business and codify it into a database filled with relational tables and fields. This stepping stone means that companies can now assimilate data from every aspect of their operations, from customers to employees. AI will turbocharge this capacity by adding extra dimensions to this data. A good example is a business being able to aggregate data, such as financial market information, from outside sources, such as stock markets, and combine them with internal ERP data to present new relationships and data points that can inform strategic decisions.

The biggest point of incidence for AI is the productivity of employees within the business. With AI capabilities applied to tasks, especially for knowledge workers, the turnaround time for such tasks is reduced significantly. This means that teams can achieve more work in less time and possibly need fewer "bodies" to achieve the same targets. This will ideally free up employees to execute more strategic roles as the mundane research-report-recommend-react and repeat cycle will be automated. The new skills of AI leveraging will dominate the landscape, and decision support will be simplified. This is because the information available will be ALL the information and not just the available sub-sets. Digital transformation will only serve to feed more information to the AI beast.

Is it all sunshine and roses? Absolutely not. Like with all new technologies, time is needed to understand the downsides. The existence of AI “hallucinations” means that AI outputs still require a healthy dose of skepticism to avoid flawed decision-making. Human wisdom still has a role to play in the enterprise, especially where empathy and emotional intelligence are required. The potential of human achievement must always be considered when planning the future, and this is rarely possible with machine learning and AI tools. Whereas human emotions can be recorded and factored into decisions, they remain erratic and unpredictable. The power of human optimism has been known to affect outcomes through sheer force of will and against many odds.

Ultimately, the enterprise must adapt to this new age and seek to leverage AI to improve and compete but at the same time not lose its soul, which comprises its people. It has been said people buy people and not products.

Chris Sang – ICT Advisory

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