This post first appeared on Forbes Technology Council.
Businesses are increasingly turning to AI to improve their critical processes and become more agile, especially in times like these when the market is constantly and rapidly changing. AI can be deployed in dozens of ways that save on time and costs, from automating back-office operations, to rapidly expanding product catalogs, to prioritizing human actions in the workplace, to increasing the speed at which a company can profitably adapt their sales strategies. It’s almost always worth it to start using AI, regardless of company size or industry, because once your enterprise is ready for AI, it’s possible to ramp up the number of automated tasks over time and save more and more in time and costs.
However, AI implementation is not instantaneous. It takes preparation to ensure that the solutions you’ve chosen for your business are the right ones and that they will be capable of benefiting your business the way you envision.
How can you tell whether your business is prepared to start leveraging AI? Answering the following questions can give you a clearer picture of where on the AI road map your business currently stands.
1. Have you migrated to the cloud?
Migrating from on-site data storage to cloud data storage might not seem like it has anything to do with AI, but it is actually the foundation of any effective digital transformation. Having data stored in the cloud can enable your business to:
1. Become faster and more agile, which is probably already a goal in the process of AI implementation. The average customer now requires on-demand service and on-demand access to products, and becoming cloud-based can make it far easier to meet those needs.
2. Become much more secure. The cloud offers enhanced reliability and security for your data and for your customers’ data as well as a more secure interface for whoever you trust to help you implement your AI solutions. Data transfer will be required, and exchanging data through the cloud is a more secure option.
2. Is your data structured?
We write a lot about data structuring because it is the key first step toward AI implementation for most companies. The average business stores a massive amount of data, and it’s often already in the cloud these days. Most of the time, however, business data is completely unstructured and, therefore, useless to even the best AI applications. AI needs to work with accessible, structured data in order to provide accurate solutions. Data that has not been categorized, tagged and carefully organized cannot be used to your advantage.
Luckily, even if an enterprise has huge data backlogs and a constant stream of incoming new data, there are efficient ways to begin organizing it thanks to auto-tagging, auto-classification solutions leveraging the latest in deep learning and machine learning customized to specific taxonomies and objectives. For example, even if your end goal is to identify objects in video files, implementing an automated data tagging solution could enable your business to leverage all of its old data and maintain useful data structures for everything that passes through the enterprise. From my experience, many businesses have backlogs of unstructured data that are growing by 55% to 65% every single year, so now is the time to start structuring.
3. Are your expectations realistic?
It’s important to have a clear understanding of your AI-driven goals and a complete plan for implementation, scaling and growth. Despite the anxiety many people and industries might feel about AI “taking over” human work and eliminating jobs, AI is actually best suited for working alongside humans and doing the work they’re not best at anyway. AI is excellent at completing repetitive tasks, prioritizing potential human actions, making small but impactful day-to-day adjustments to processes and cutting down on the kinds of errors that can slow businesses down, reduce precision and predictability and necessitate wasteful rework by expensive human resources. When AI is properly leveraged, it can actually free up human employees to do what they’re best at — creative problem-solving and innovation.
Since most businesses face some degree of uncertainty in the current market, one goal of your AI implementation strategy should be to enable continuous improvement and scalability. AI can work by employing ongoing machine learning capabilities that allow the solution to adapt to new data and new circumstances at any time. These feedback loops allow for self-adjustments that ensure continued accuracy even in the face of sudden change.
As AI grows more common and the market continues to change, almost every type of business will be forced to turn to AI to ensure success, enable growth and remain relevant to their new and existing customers. When AI is leveraged the right way with solid foundations and expectations, it can help businesses reach their full potential.
