We’ve just been dropped into the jungle. We’re surrounded by trees. It’s raining. We have no map. No umbrella. No snacks! And is that a prowling jungle cat I hear in the distance…?

In the jungle, that is generative artificial intelligence (AI) many of us have reacted with a ‘"fight or flight”’ response. But we’re here to tell you how you can safely prepare for gen AI in your organization without getting lost in the data privacy weeds.

We’re seeing a life-altering technological-race afoot with the launch of ChatGPT, DALL-E, Copilot and other generative AI software, and this is spurring business leaders to look at how they can safely and effectively use this emerging technology in their enterprise.

Like the printing press and the written word before it, experts and laypeople alike are concerned about where generative AI is headed.

So, the question is, do we accept this so-called ‘disruptive technology’ and find ways to use it, or do we run in the other direction and hope it doesn’t catch up?

Technology is an ever-evolving and expanding field that will inevitably change the future of work.

There’s currently a lot of hype around generative AI, so let’s clear some things up. We’re going to help prepare you for generative AI with a packing list of what you need, what to look out for and how best to prepare your business.

Why Is Generative AI Important?

Okay, so why is generative AI so important? At this point in history, that’s kind of like asking, “Why is the internet important?”

Generative AI is one of those high-impact technologies marking a pivotal shift in how work is done, how data is accessed and how the future of rapidly growing technologies will look.

Gen AI solves challenges across industries when combined with intelligent automation (IA) solutions, from speeding up the time to new medicine development and faster disease diagnoses, to improving education and communication, to making people’s jobs more interesting and meaningful. There are even fiscal benefits for companies seen in cost savings and improved operational efficiency. And the scope of generative AI is evolving to go beyond economic benefits, with the potential to tackle big-ticket issues like climate change and education inequality.

Already organizations are using IA to automate workflows and business processes, removing time-consuming and repetitive tasks from their employees’ workloads so they can focus on higher-value, strategic initiatives.

With generative AI, there are even more automation options to explore.

So, yeah. It’s important. But let’s jump into what it is before we explain how you can use it.

What is generative AI?

Generative AI refers to a subset of AI that focuses on creating or generating new and original content such as images, text, music, software code, etc. It works by training machine learning models to learn patterns from existing data and then uses that to produce novel and realistic outputs resembling the original data.

Already you can see where issues arise regarding intellectual property and copyright infringement. Since generative AI is still a relatively new field, governance and regulations are racing to catch up – an important consideration for any organization wanting to bring this technology into their business processes.

What is AI?

Artificial intelligence (AI) is the development of computer systems or machines to perform tasks that mimic human intelligence.

AI is often considered the ‘thinking’ part of a technology and can involve a range of technologies including machine learning (ML), natural language processing (NLP), computer vision and more. These added technologies enable AI systems to analyze and process vast datasets, recognize patterns, make predictions and aid in decision-making.

What is intelligent automation?

Intelligent automation (IA) encompasses AI technologies with robotic process automation (RPA), business process management (BPM) and others, to deploy digital workers that can optimize various business processes.

There are various automation options for organizations depending on their business goals. IA goes beyond standard rules-based automation to handle unstructured data, make informed decisions and perform complex tasks.

How to Prepare for Generative AI

Here are some preparation tasks you’ll have when introducing gen AI to your organization: 

1. Reframe your thinking. 

Rather than seeing it as the existential robot takeover we’ve seen in so many great films, recognize its potential: Generative AI is a tool meant to help you with brainstorming, freeing up valuable time, identifying errors and inefficiencies, and so on.

2. Educate yourself and your people

If you can get your organization on board and willing to learn about this technology, it’ll help you stand out from the competition. Encourage your people to try out generative AI programs so they can then brainstorm its uses within the business.

3. Identify and discuss the effects

Consider generative AI’s strengths, limitations and ethical considerations. Go through the possibilities – the good and the bad – of what generative AI can do, identifying the potential benefits and the vulnerabilities so you’re prepared if they arise.

4. Know the risks

There are plenty of risks associated with generative AI, including ESG regulations, bias, fabricated results, copyright and privacy violations, and leaked data. Ensure you have the right people, resources, guidelines and business models before jumping into the technology.

5. Brainstorm use cases

Identify specific areas within your organization where generative AI use cases can bring value. Consider the levels of automation generative AI can enhance to streamline existing processes, generate new ideas or solve complex problems.

6. Find suitable AI tools

Generative AI has a long list of assets, one among them being its ability to summarize large datasets of information into condensed, bite-sized pieces. Imagine how much time that one application could save, or how many mundane tasks can be removed from your employees’ workload. Think about how your employees can interact with gen AI tools as if they were digital colleagues rather than rivals.

7. Prepare your infrastructure

Before introducing generative AI into your organization, you need ensure your systems can handle it. While going through these preparation tasks, consider the data quality, amount and content you would use to train your generative AI program and ensure you have the technology to handle the computational requirements.

8. Find skilled people

Once you have an idea of how you’ll use generative AI, you need experts to help ensure best practices in development, training and deployment.

9. Establish governance

Consider the ethical quandaries that may arise with generative AI, such as biases and data privacy. Develop a clear framework to address these potential disruptions and set a standard to ensure the technology consistently aligns with your business goals and values.

10. Set up regulatory rules

To ensure your organization maintains compliance, your generative AI tools should always be informed of the latest legal and regulatory requirements regarding data usage, privacy and intellectual privacy rights. You may want to introduce a Center of Excellence (CoE) team to help with this.

11. Test and train

 Start small and experiment with generative AI in a safe and tested model development environment. This will help improve its performance and identify any limitations and improvement opportunities.

12. Join a community

 Find a community of like-minded individuals and business leaders interested in generative AI to learn best practices and brainstorm its growth potential.

13. Evolve and adapt to AI

 Generative AI is an evolving field, so it’s important for organizations to stay up to date on the latest industry trends, research and advancements. Foster a culture of continuous education within your organization and encourage people to think about business opportunities with generative AI.

Generative AI – A Good Disruption

Some see generative AI as a fast-moving disruption to the way people work. But like most things, if gen AI is used with care, consideration and good planning, it has a lot of potential.

While task-automating technologies like robotic process automation (RPA) have a narrow intelligence – meaning they focus on individual tasks as they’re assigned to them – introducing generative AI into the field of automation carries a new level of progress and potential for organizations.

From business growth to improved customer and employee satisfaction and beyond, we’re only just scratching the surface of generative AI’s benefits for companies. And we’ll likely see this advancement tackled in larger-scale areas in the future to meet the economic and technological demands of the evolving era.