Adopting IT Advances: Artificial Intelligence and Real Challenges – CIO Applications

By coming together, we are able to select and strengthen a business process supported by advanced analytics, which local teams can embrace and deploy across their business units.

In addition to the benefits of forming a cross functional, multi-national team, its been exciting to watch the collaborative process evolve as Baby Boomers, Gen X, Gen Y and Gen Z colleagues work to solve business critical challenges. Weve found that by bringing these generations together, we can leverage the necessary experiences and skillsets to create a balanced vision that forms the strategy as the work streams begin to develop their actions. Pairing the multi-generational workforce with our focus on inclusion and diversity also fosters internal ownership. This participation yield steam unity and pride through clearly understood program goals, objectives and--ultimately--improved adoption deep across all business regions.

Build confidence

Even with a global, inter-generational team building advanced applications, theres still a question of confidence in the information delivered through AI and ML techniques. Can the information being provided actually be used to create a better, more reliable experience for our customers?

A recent article by Towards Data Science, an online organization for data scientists and ML engineers, put it best: At the end of the day, one of the most important jobs any data scientist has is to help people trust an algorithm that they most likely dont completely understand.

To build that trust, the heavy lifting done early in the process must contain algorithms and mathematical calculations that deliver correct information while being agile enough to also capture the changes experienced on a very dynamic basis in our business. This step begins further upstream in the process by first establishing a cross-functional group that owns, validates and organizes the data sets needed for accurate outputs. This team also holds the responsibility for all modifications made post-implementation as continuous improvement steps are added into the data driven process. While deploying this step may delay time to market delivery, the benefits gained by providing a dependable output decreases the need for rework and increases user reliability.

Time matters

How flexible is your business? It takes time and dedication to successfully incorporate AI and ML into an organization since it requires the ability to respond quickly.

Business complexity has evolved over the years along customers increasing expectations for excellence. Our organization continues reaching new heights by deploying AI and ML techniques that include an integration that: Creates a diverse pool of talented external candidates Leads to stronger training and development processes and programs for our employees Localizes a global application Bridges technological enhancements with business processes Drives business value from delivering reliable information

By putting the right processes in place now, forward-thinking businesses are better prepared for a quicker response when tackling IT challenges and on the path to finding very real solutions.