Making decisions is what leaders do at the right cadence, at a defined target, and within an achievable, realistic timeline.

Artificial Intelligence in business decision making does not change the fact that decisions need to be made. What will change is how often we will make strategic decisions and how we will measure the performance of tactical compliance.

Intelligent systems for decision making in business will offer business leaders insight that until now hasn’t existed. The cadence of decisions will continue to increase in the boardroom and will require tactical decisions and processes to align quickly. Leaders will need to acknowledge the two pillars that will shift in the coming years and decades. First, artificial intelligence systems will shift further from only making tactical decisions to making more strategic ones.  Human leadership from the bottom-up will shift from carrying out repetitive menial tasks to being required to ensure processes are aligned and in the future “leading” AI.  Second, as mentioned before, the modern leader will mandate compliance with tactical processes with an increased cadence. Top-down decisions will only be as effective as the organization’s ability to implement, so measuring the performance of compliance to the success within the market allows leaders to immediately gauge the accuracy of that decision.  

Business decisions using AI will give leaders more direct control of their processes.  It will be the modern leaders with technical and data literacy that will have the skills to navigate and ensure performance is managed within their workflows. It’s here where the most significant challenges and shifts of effort will occur. As demand for the frequency of strategic decisions increases, organizations that cannot align their culture and skillsets within lower management will not be able to keep up and will eventually lose the ability to compete. The realignment of the organization requires a highly cohesive bottom-up method to measure “pivot performance.” Pivot performance provides visibility to good strategic decisions executed optimally at all levels. Pivot performance is measurable to the bottom line and identifies the inequality of outcomes that drag on its potential.   

Revolution of AI in Business Decision Making

The role of artificial intelligence in the business decision-making process is implemented both top-down and bottom-up. Modern leaders should demand highly relevant information pre- and post-decision at all levels of the organization.

Top-down – Leaders will have the right information to ensure their decisions are being carried out at the macro-level. This might sound like information overkill, however, when a method of inequality management is deployed, executives can visualize the impact of their decisions and where there is weakness vs. robust compliance. Within compliance, the best results should be found. This closed-loop removes the barriers to measuring strategic decisions, therefore, allowing more decisions to be made with higher precision.

Bottom-up – Decision-making techniques will require leaders to consistently identify opportunities and execute changes in processes and tasks within their personnel and technologies. Organizational culture must accept and support the ongoing desire of managers to improve and redefine workflows more often. Leaders that can identify weak processes within the chain, even when these processes could be outside their control, will rise to the challenge and fill the ranks of successful upper management in the years to come.

Benefits of Artificial Intelligence Technology in Business Transformation

Machine learning as it evolves into true AI is a potent stream of technology that can align three prominent needs of business: automating business processes, gaining insight via data analysis, and creating an interactive work culture by engaging employees and customers. Emerging technologies fueled by machine learning is giving birth to AI. Technology will now evolve organically with us.

Tallgrass.ai solutions can help any business define the change required and create the roadmap to successfully adopt these emerging technologies. Business decision-making solutions require a top-down commitment to change. Before machine learning and intelligent processes can thrive, the economic landscape should be fully understood and the company’s direction sound.   These tasks are not technical hurdles, but cultural. Companies that are able to define their optimal purpose and can quickly align processes will dominate their market.  

Data Analysis

We all acknowledge the past holds the keys to our future. This has never been more true as the past is providing more insight today than when it was created.  Machine learning can literally iterate through history until optimal outcomes are discovered. The value only starts there – once we know the true performance of a decision we can monetize its impact. 

Marketing Decisions

In today’s customer-driven industry, it is essential to utilize a data-driven decision-making solution. Customer-driven complexities involve understanding the requirements and desires of customers and aligning products to customer’s behavior. Having full knowledge of constantly changing customer behaviors and trends aid the optimum business decision process. AI modeling and simulation methodologies reflect reliable insight into the consumer’s character. Other multiple AI forces also assist in making well-informed marketing decisions such as data gathering, trend analysis, and forecasting.

Immediate Satisfaction, Product Mixing 2.0 

In today’s demand-driven markets, we are all used to getting immediate answers to our searches and queries. In-kind, we have been tuned to demand more and more unique products and services. Uniqueness carries an increased amount of value and the markets are demanding it, but who is really listening? Some companies have learned to leverage this demand and have even created a workflow to fragment markets into smaller niches where they are winning domain authority. 

It takes a lot of focused energy to influence and carve out your own market. Knowing your customer is only the start. You need to understand the potential market that “should be” your customer. Who are the influencers? What can be learned and quickly leveraged to build loyalty and credibility?

Accurate product mixing is a science within itself and provides organizations options to build a deep loyalty with current customers and gain an advantage with new ones.   Most if not all businesses get product mixing wrong. Not because they lack relevant products and services but how they rank their perceived value to the market. The right balance of value has to match the least amount of effort to produce it. Products and services take different time and energy to produce to customers and between suppliers. Some suppliers will produce higher quality products for less effort and be in a position to discount or even give away the core products of their competitors.

Conclusion

When a common culture for top-down decision making has cohesion and control to optimize outcomes of artificial intelligence, it will foster a complete business transformation.