Master These Elements For A Successful AI Transformations Of Your Enterprise

Aashish Kalra

The age of Artificial Intelligence(AI) has already arrived and the discussion is now shifted towards the expectations and implementation now. AI solutions are coming at a breakneck speed and companies are finding it tough to design a right AI strategy.

Businesses that have started or looking to adopt AI technologies to create intelligent systems that can learn and adapt and later execute the predefined instructions. Different businesses are looking to adapt AI technologies in different processes. Healthcare, energy and utilities and data infrastructure are aggressively looking to develop AI solutions to remove manual processes of data cleansing, preparation and predicting results on case to case basis. In the healthcare industry, “computer-assisted diagnosis” helps to spot 52% of the breast cancers based on mammography scans one or two years before women were officially diagnosed.

Similarly, in the space of data security and infrastructure, a lot of work is going on to make cyber security less prone to increased cyber-attacks. The latest cyber-attacks and malware have an access to updated new-gen technologies and rectifying them is not possible with conventional cyber security protocols. AI/ML based security solutions rely on data from past cyber-attacks and respond quickly by identifying them.

Likewise, energy savings based on rising demand and consumption can be predicted with past data, ability to store and apply statistical model and creating self-smart systems. These concepts are no more foreign to organizations that have sensed that the future of AI driven business world. The availability of extensive parallel processing power, advanced algorithms and massive data sets to feed the algorithms has made it possible for AI to venture into reality.

Even though the world is transforming at a rapid pace, there are some businesses that are outliers in the AI space and AI creates two halves of haves and have-nots’ in the AI space. There will be businesses with resources to implement AI solutions and use AI to get to decisions, and there will be businesses still standing in the ‘have-not’ space. The businesses that are trying to shift from have not to have space need to consider following elements to make AI implementation successful.

AI Transformations in the Enterprise: Elements that matter

The elements of successful AI transformations are data ecosystems, improvements in data capturing and management, capacity and bandwidth of cloud solutions, improved models and techniques, right talent pool and organizational intent. Successful AI transformations require companies to be mature in analytics and digital aspects.

Big Data

Data is the next natural resource, like air, oil and water. The capability of data gathering has evolved for and businesses have dashboards for tracking KPIs, metrics and data visualizations. The data has been gathered more and utilized less and thus multi-billion dollar opportunity exists for AI and Big Data.

Cloud Solutions

The successful implementation of AI largely depends on the organization’s capacity to use hybrid cloud

Platforms that can provide faster data processing without lag time and capacity to handle high volumes

Of real-time data. Albeit, businesses cannot just let go their legacy structures in one shot and AI solutions need to work with their existing business technologies and work as a package to improve core functions.

Talent Pool

AI race is going to be tougher than we imagine and companies with right talent pool is going to win the race. This is further strengthened by Gartner’s prediction that by 2019 startups will overtake Amazon, IBM, Microsoft and Google in driving the artificial intelligence economy with disruptive business solutions. Startups come with new breed of IT professionals that are skilled to develop solutions that can uberized the new burgeoning AI economy.

Organizational Intent

Organizational intent towards adoption of AI is one of the most crucial element of successful AI transformation. Successful AI transformations need to change business processes that are working in silos and collaborated with processes looking for AI makeover. Decision-making and goal-setting for AI initiatives are going to be efficient in top down approach in the organizations.

Businesses to evolve in AI and become more generalized, have to shift from a stand-alone to a collaborative model in which data communicate with one another and act in concert to accomplish tasks. However, management issues such as liability and privacy, along with the complexity of handling such projects are to be leaded by C-suite to be an AI-first company.

The author is Chairman, Cambridge Technology Enterprises Limited