5 Adoption Essentials For Enterprise Success

5 Adoption Essentials For Enterprise Success


Anyone paying attention to business and technology knows that AI is already driving seismic waves of change in industry and day-to-day life. It’s no longer a futuristic concept but a present-day reality with profound, multi-trillion-dollar implications. In fact, according to PwC, AI is set to add up to $15 trillion to the global economy by 2030.

However, although its reach and influence is undoubtedly growing, many businesses and organizations are still struggling to implement it effectively. In my own experience working with global businesses to deploy AI and data-driven initiatives, I’ve found that this often comes down to a lack of preparation. In many cases, the eagerness (or fear of missing out) often means that the groundwork needed to ensure a stable foundation is skipped, rushed or overlooked.

So, here I will try and highlight what I believe are the key ingredients of this essential preparatory phase. This includes five areas where preparation will significantly enhance the overall value, impact and chance of success for any organizations setting out to embrace AI.

1. Aligning AI Strategy With Business Goals

Let’s start with perhaps the most important message – AI strategy should always be aligned with solid business goals. There’s a huge amount of hype around AI at the moment and a great deal of FOMO (Fear Of Missing Out). But a decision to deploy AI shouldn’t be driven by this, but rather by its ability to solve your own specific problems.

Binance

This means that decision-makers must be able to identify priorities as well as have a broad understanding of how AI (or any technology they are considering) can address them.

AI has the potential to improve just about any aspect of business performance or improve any metric. Your own specific challenges might involve generating profits or growth, improving customer satisfaction, innovating in product and service development, reducing waste or improving sustainability.

An example of a well-known business that get the strategic use of AI right is Amazon, which drives customer experience with product recommendations and efficient logistics. Another is Netflix, which creates personalized content recommendations designed to keep us subscribed.

In the AI age, businesses will sink or swim depending on their ability to identify the problems that matter, and match them with solutions. Ensuring these skills are in place among leadership teams and decision-makers is a crucial element of preparedness.

2. Cultivating An AI-Friendly Culture

It’s natural and unavoidable that some people are apprehensive or outright hostile towards AI. Any business hoping to benefit from it has to understand that as well as the technology challenges, there are questions around ethics and societal implications that have to be addressed.

To do this, businesses can implement strategies and processes that aim to educate employees about AI. The key is demonstrating how it will augment and assist, rather than replace us.

As AI pioneer and professor Yoshua Bengio puts it, “The value of AI in the workplace goes beyond automation. It is about augmenting human intelligence, enabling workers to make better decisions, and fostering a culture of innovation and problem-solving.”

This cultural aspect is critical. The ethos around business AI intrinsically involves experimentation and trying new things to see what works. If a company has a culture where this is rewarded and celebrated, it’s well-placed to benefit from the AI revolution.

3. Skills And Expertise

Having the right skills in place is another crucial piece of groundwork, and that could mean hiring new people, upskilling existing ones, or building partnerships with other businesses that can help.

As Matt Hicks, CEO of Red Hat, told me when I spoke to him recently on my podcast, “Finding those partners that are going to help guide you through that, I think, for most companies, is pretty critical – otherwise they could just waste time in the experimental phase.”

While partnering with experts can accelerate the learning curve, for many organizations there’s also a need to create an ecosystem that supports continuous learning and skills development. Things change fast in this field and workforces need to be prepared not just for what’s happening now but what’s around the corner.

4. Ethics And Trust

In order to be ready to benefit from AI, businesses must understand and have answers to the ethical questions it creates. What implications does AI have for the humans that make up both the customer base and the workforce? What will be its impact on privacy? What are the dangers of AI bias and how do we mitigate them?

This means committing to ethical practices and will often necessitate the development of formal internal policies and guidelines. Having processes in place to regularly audit and review how AI is being used and the impact it is having is essential.

ChatGPT creators OpenAI put guardrails in place to minimize the risk of its products being used to cause societal harm – by enabling violence, hatred or discrimination, for example.

As time goes on its likely that these standards will shift. So it’s important to have procedures in place to understand how the impact of AI on our lives is evolving, and adapt our policies and guardrails to fit those changes.

5. Data Management And Protection

Data is the fuel of AI, and in order for it to be effective, our data has to be robust, comprehensive and clean. Inevitably this involves technical data management skills

Whether we work with information that’s held on premises or in the cloud, or take a hybrid approach, businesses must have an understanding of the technical aspects of collecting, storing and processing vast quantities of data.

As Hicks points out, today anyone can use an AI chatbot interface to start leveraging AI. Those that want to lead, however, must be able to differentiate themselves. From a technical perspective this means having better, more efficient and more robust data and analytics infrastructure.

We also have to be capable of keeping it safe. Particularly when storing personal data (often the most valuable data), allowing the possibility of a breach can lead to harsh business and regulatory penalties, as well as catastrophic loss of customer trust.

This involves having stringent data governance policies in place that address privacy as well as regulatory concerns, as well as provide clear protocols for data storage, collection and sharing.

Ultimately, a mature and robust approach to data management is a key element of ensuring a business or organization is ready to reap the benefits of AI.



Source link

Leave a Reply

Your email address will not be published. Required fields are marked *

Pin It on Pinterest