A Smarter Tomorrow: How Real-time AI Revolutionizes Business Decisions

Better data equates to better decisions. Businesses across many industries are getting smarter in allocating resources and making big decisions thanks to technological insights. Today, most business managers feel completely handicapped without access to analytics. This is only the start. Artificial intelligence (AI) has entered the fray with the promise to drive business through predictions, recommendations and decision scoring. Welcome to the world of real-time AI for business leaders – a revolution without precedent. 

Integrating AI

So, just how does real-time AI integration help make better business decisions? By unlocking machine power to predict, recommend and score business decisions for any industry. Rather than looking at a problem from a historical perspective, AI uses the past to objectively look forward and deliver business intelligence as and when needed.

It is helpful to consider this in the context of American football, which uses analytics to drive decisions and, like a business, improves decision-making by analyzing past successes and failures. For example, plenty of football teams go for a first down on fourth-and-one situations because analytics says so. Real-time AI takes this situation to a completely different level. For this situation, rather than rely on analytics to pre-define the approach on fourth-and-ones, real-time AI analyzes the specific situation, including the team, the defensive players on the field, as well as the coach, position on the field, score, weather and more to recommend decisions relevant to the specific situation. It is like having the best coach in the NFL with the uncanny ability to access and process a lot of past data whispering in your ear when you have to make that fourth-and-one call. 

The ability to do this for business should speak for itself.  

Data-Based Decisions

AI-driven business decisions are the future. There was a time when companies put in hours and days of work to formulate business insights. The advent of computers and data analysis and analytics capabilities changed business decision-making via dashboards. AI takes it to the next level by providing predictions and recommendations to help with the decision-making. In addition to just the analytics, AI provides intelligence in real-time when it is needed by the person making the decision.

AI has the potential to replace rigid, rule-based models and make the process dynamic. For example, many applications for insurance and loans are based on a predefined set of rules. In an AI-driven business-decision world, these models are dynamic and learn from the results to continuously refine the decision-making process. Fraud and intrusion detection systems, for example, already use machines instead of humans, as do operations such as call centers where chatbots are the first line of defense. In the years ahead, expect AI to become mainstream at most forward-looking industries and companies, and just like today, those companies that don’t provide their managers with easy access to analytics will find themselves at a competitive disadvantage.

Let’s look at an example. Today, most sales organizations work with a defined set of stages, assign a probability to each and drive the pipeline with this philosophy. Some companies even drive their street forecasts with this approach. With real-time AI assistance, each opportunity can receive a score to create a dynamic sales funnel that continuously helps sales managers prioritize the pipeline. Real-time AI also gives sales managers predictions and recommendations to engage the customer, which increases the likelihood of closure. Essentially, it enables managers to focus on the top 20% of customers, which leads to 80% of sales.

AI, which is already changing the marketing sector, heralds the dawn of targeted customer acquisition and engagement: the ability to reach the right customer for the right product at the right time with the right message. It essentially replaces the broadcast marketing approach with a personalized message for every customer. And the best is still to come. 

Knowledge Today for Tomorrow

The potential of AI-driven business decisions is unlimited; the technology provides business leaders with decision-making support and intelligence as never seen before. So, what are the key steps managers can take today to prepare for the AI business revolution?

First, start with the business problem. Most organizations have data science and machine-learning teams to find new insights or models that the business can use. However, this must be reversed. Technology is the enabler, but it must be concentrated in the right direction.

Second, find or acquire the right data, both internal and external. It is critical to have both for models to work effectively. This may also be an opportunity to review what other data you need within your organization, and either digitize it or create derived data elements. The real potential of these technologies comes when you bring external data to complete the picture.

Third, pick the right model. Machine learning and deep learning algorithms are not one-size-fits-all solutions. There are many algorithmic options that leaders can incorporate for their problem. Again, while technology may do the heavy lifting of building the models, this needs to be a business-driven step, and all results need to be analyzed for business accuracy.

Lastly, learn and improve. The learning and improving capabilities of AI technologies is their key strength. Systems that continuously learn assures that predictions and recommendations will be better than the last ones. Businesses must implement a supervised feedback loop to ensure their decision systems are learning and becoming better. 

Businesses that capitalize on the potential of today for the possibility of tomorrow will be best placed to benefit from the revolution in business decision-making. It all depends on whether individual leaders are ready to take the plunge.