Buying Advice to Tackle AI Trust, Risk, and Security Management

In this technologically dominated era, the integration of artificial intelligence (AI) has become a trend in numerous industries across the globe. With this development of technology, AI brings potential risks like malicious attacks, data leakage, and tampering.

Thus, companies are going beyond traditional security measures and developing technology to secure AI applications and services and ensure they are ethical and secure. This revolutionary discipline and framework is known as AI Trust, Risk, and Security Management (AI TRiSM), which makes AI models reliable, trustworthy, private, and secure.

In this article, we will explore how chief information security officers (CISOs) can strategize an AI-TRiSM environment in the workplace.

Five Steps on How C-suite Can Promote Trustworthy AI in Their Organization 

The emergence of new technologies is likely to drive more potential risks; however, with the help of these five essential steps, CISOs and their teams can promote AI TRiSM solutions:

Defining AI Trust Across Different Departments

At its core, AI trust is the confidence that employees and other stakeholders have in a company that governs its digital assets. AI trust is driven by data accessibility, transparency, reliability, security, privacy, control, ethics, and responsibility. A CISO’s role is to educate employees on the concept of AI trust and how it is established inside a company, which differs depending on the industry and stakeholders. 

Develop an AI trust framework that helps achieve your organization’s strategic goals, such as improving customer connections, maximizing operational excellence, and empowering business processes that are essential to your value proposition. Once built, implement methods for measuring and improving your AI trust performance over time.

Ensure a Collaborative Leadership Mindset

As IT organizations rely on technology for back-office operations and customer-facing applications, IT leaders face the challenge of balancing business and technical risks, potentially leading to prioritizing one over the other.

CISOs and IT experts should evaluate the data risks and vulnerabilities that may exist in various business processes, such as finance, procurement, employee benefits, marketing, and other operations. For example, marketing and cybersecurity professionals might collaborate to determine what consumer data can be safely extracted, how it can be safeguarded, and how to communicate with customers accordingly.

As a CISO, you can adopt a federated model of accountability for AI trust that unites the C-suite around the common objective of seamless operation without hampering customers’ and organizations’ data. 

In conclusion, as businesses grapple with growing datasets and complicated regulatory environments, AI emerges as a powerful tool for overcoming these issues, ensuring efficiency and dependability in risk management and compliance. AI Trust, Risk, and Security Management (AI TRiSM) may assist businesses in protecting their AI applications and services from possible threats while ensuring they are utilized responsibly and compliantly.
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The Rise of Low-Code and No-Code Solutions in Business

For many years, there have been two routes that businesses take on their way to application development: buying ready-made apps from an external vendor or building these apps from scratch using skilled developers and codes.

However, in the last few decades, the scenarios have changed with the rise and growth of sophisticated low-code/no-code (LC/NC) development. This is a great alternative that brings the power of application development to users across different industries.

Further, low-code/no-code (LC/NC) applications provide a close fit to different business requirements, as they can be implemented quickly and cost much less than a system developed in-house.

So, the use of LCNC tools brings the potential for increased user accessibility, which promotes more innovation and relieves the load on IT departments. The adoption of LCNC platforms is the next step in making application development simple and accessible to everyone.

In this article, we will explore more about low-code and no-code through use cases and how they can benefit your business.

What is Low-code?

Low-code is a way of designing and building programs that use simple graphical tools and embedded functionality to eliminate the need for traditional or pro-code writing. Users may reduce their workload by utilizing low-code platforms that use tools to speed up and simplify certain operations. Examples include testing, troubleshooting, and development. These low-code app development platforms walk users through the process of building an app with tools.

What is No-code?

As the name implies, no-code does not require any code.  No-code app development platforms have pre-designed interfaces, which users may customize using visual tools. This enables non-technical business users to create apps without writing a single line of code. 

How Do Low-code and No-code Tools Work?

The foundation of low-code development platforms (LCDPs) and no-code development platforms (NCDPs) is built on the ideas of visual programming, model-driven design, and automated code generation. Regardless of coding skills, these platforms are purposefully made to appeal to non-technical users who are acquainted with the procedures and workflows inside their business department.

According to a recent Gartner survey, by 2024, almost 65% of applications developed globally will leverage LCNC platforms. The predicted growth rate for this is a sharp 165% per two years. So, when businesses start using LCNC technologies, the number and complexity of non-technical users rapidly increase as individuals realize the value of quick and precise app creation in nearly any business field.

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