AI PlanAI is taking center stage across a wide variety of industries, including retail and manufacturing

Artificial Intelligence is clearly a growing force in the business sector. Recently, AI has broken the wrong perspective of many executives and business owners that it is applicable just too big companies like Facebook, Apple, Amazon, Netflix, and Google. It is serving every corner possible when it comes to showing its potential. AI is taking center stage across a wide variety of industries, including retail and manufacturing. New products are being embedded with virtual assistants, while chatbots are answering customer questions on everything from online office supplier’s sites to web hosting service provider’s support pages. AI has made widespread advancements through its applications such as machine learning, computer vision, deep learning, and natural language processing (NLP). Here are some of the tips that companies should follow to adopt AI. 

Keep your Expectations Moderate

You shouldn’t resist AI because the things it can do can really help your business. But don’t expect it to solve all your problems. AI and particularly machine learning gets smarter the more it's used. So be patient.

Bring More People 

Like any other contributing factor to your business, you need to have an indicator of success. Don’t just “get AI.” Identify where AI can help you achieve your goals and implement it to do that. AI needs developers and they need to be developers that understand how AI really works and how it impacts security. Hire or train people to think about how to train AI and how to defend against it too

Get Familiar With AI

Take the time to become familiar with what modern AI can do. You should also take advantage of the wealth of online information and resources available to familiarize yourself with the basic concepts of AI. It is recommended that some of the remote workshops and online courses offered by organizations such as Udacity are easy ways to get started with AI and to increase your knowledge of areas such as ML and predictive analytics within your organization.

Acknowledge the Internal Capability Gap

There's a stark difference between what you want to accomplish and what you have the organizational ability to actually achieve within a given time frame. It is said that a business should know what it's capable of and what it's not from a tech and business process perspective before launching into a full-blown AI implementation.

Spend Time on Change Management and training

Deploying an AI API to ingest a new dataset is straightforward. However, altering the management and training for analysts who’ll be using these processes going forward is a challenge. Most forms of AI create automated decisions – “yes” or “no.” However, it is often the case that the integration of ML algorithms can allow for more subtle responses as well. These responses may be used in conjunction with existing processes to deliver the best results. 

Consolidate and assimilate automation

As you ramp up enterprise-wide AI adoption, what these processes look like in the future will change with the introduction of a multitude of types of automation. From complete manual processes all the way to the adoption of RPA, and even more advanced AI protocols. It’s best to just (and I know it’s a big just) re-invent business processes from the ground up with AI in mind. You can then apply the best tool for the job at any given step.

Plan for the Impact

Using AI may or may not shift jobs around in your company or even eliminate some. It most definitely may try to use data in unanticipated ways. Make sure you anticipate that and head off any embarrassing, or even troubling, privacy implications or employment crises.