5 Biggest Challenges in Implementation of AI into Business Processes

In recent years, we all have heard about AI and its possible implications in different domains. But implanting or adopting it is still narrow in many business or different industries. Adopting Artificial Intelligence technologies offers many benefits to the organization but implanting it create lots of challenges.

Despite the recent developments in AI technologies, most of the organizations are on the early stage of adoption of these technologies. There a lot more to do with AI in business organization. Organizations need to visualize the AI learning curve and its impact on the business performance.

Before implementing AI into business, an organization need to understand the issues involved and possible risks associated with Artificial Intelligence against the benefits received by the company with the use of AI in different business processes.

5 Major Challenges involved in implementation of AI

Inadequate skills set

Implementation of AI in business processes requires feasibility as per the organizations resources. Many organizations are lacking with the skill sets and competencies to operated AI based solutions. AI is eating redundant jobs but opening many new opportunities. But the biggest challenge is organizations are lacking in data science skills to leverage AI assisted benefits and maximize the values of emerging AI based solutions.

Risk of data leakages

Automation in each process create issues related to data privacy which imposes ethical and legal challenges for the organization in implementing AI. With the increasing use of technology and data driven approach create issue related to data privacy and breach of privacy can have legal consequences on the organization.

Ample amount of data availability

To implement AI fully in the organization required huge data sets which are labelled and authentic source of data. Now a day's organizations are bombarded with huge data but to what extent they are labelled to train and teach AI is not sure. Inappropriate data feed can cause error in AI assisted outcomes. As the decision making by artificial intelligence is a data driven approach to business management. So, the organization make sure that AI based systems should be feed with the right data and at the right time to leverage its benefits.

Complex algorithms

The function and performance are highly dependent on algorithms and the neural networks. An organization need to have clarity how AI is going to impact the business outcomes before extending its applications. Understanding the complex algorithms will reduce the legal and regulatory challenges to the organization.

Identifying the reason of AI outcomes

One of the biggest issue in the implementation of AI in different business processes is that AI comes with the result and solutions based on the algorithms programmed and neural networks. But it is difficult to understand how AI came to this conclusion or why AI given this particular result. Because organization have to be accountable to its stakeholders for any actions of it if something goes wrong.

Everything has two side of the coin one is good and another is bad. Similarly implementing AI results in both create many issues and provide advantageous position to the organization. So, organization should understand the challenges to minimize the risk and maximize the benefits of adopting AI in its processes.

Source: HOB

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