Artificial intelligence has undergone significant development in the past few years. It started with Narrow, then moved towards predictive, and now has reached the generative AI state. All these advancements allow digital transformation and disruption across industries. Apart from helping improve digital customer and omnichannel experiences, it also helps synergize other technologies, including automation, the Internet of Things (IoT), big data and analytics, cloud, and cybersecurity. These AI solutions assist with operations, infrastructure, end-to-end data management, decision intelligence, risk, and compliance. AI solutions are also contributing to strategic planning, human resource management, marketing, and supply chain functions.
Organizations that want to improve their overall quality, accuracy, compliance, acceptance, reputation, resilience, and cost-effectiveness in their AI solutions, must focus on the ethos of AI TRiSM.
Here is a deep dive into the world of AI TRiSM so that you can incorporate it into your work culture.
What is Artificial Intelligence?
Artificial Intelligence is the new technology aimed at giving machines the power to simulate human intelligence and problem-solving capabilities. Some of the major applications of AI solutions include expert systems, natural language processing, and problem-solving capabilities. Today, AI/ML services provider companies are offering AI as a service to organizations that want to become better faster.
What's AI Trust, Risk, and Security Management (AI TRiSM)?
Today, businesses are experiencing a complex interaction of interconnected and loosely coupled organizations, facilitating improved velocity and diversity across heterogeneous datasets.
AI app development companies are also noticing an increase in the overall algorithmic biases, potential risks, and vulnerabilities. Internal and external stakeholders are also asking for more transparency, inclusion, explicability, and ethics. This is where AI TRiSM comes into play.
Artificial Intelligence Trust, Risk, and Security Management (AI TRiSM) is a comprehensive framework made to manage the challenges associated with AI systems, allowing for improved fairness, efficacy, reliability, governance, and privacy.
A Deep Dive into the AI TRiSM Framework
AI TRiSM Framework stands on four pillars, namely.
Explainability
This pillar is focused on creating a more transparent system, allowing clearer explanations by the AI models for their decisions and predictions. For this to work, AI models must be regularly monitored, ensuring that no biases are introduced into the system.
Model operations
Model operations include processes and systems creations to manage AI models throughout the lifecycle, including development, deployment and maintenance. It includes the maintenance of infrastructure and environment to ensure that the models run optimally.
AI application security
Every AI development company works with secure data, and security breaches can have serious consequences. Therefore, application security is essential to keep the model secure against cyber threats. The AI TRiSM helps create security protocols to safeguard AI algorithms against tampering.
Model privacy
Privacy models ensure data protection when training and testing AI models. AI TRiSM framework assists AI services company with creating policies and procedures to gather, store, and use data in a manner that protects individuals’ privacy rights.
How Can Organizations Utilize AI TRiSM?
AI algorithms can be used for both bad and good. The fact that they are more prone to cyberattacks means that cybercriminals can attack these models to automate and optimize malicious processes, including malware attacks, data breaches, and phishing scams.
With over 236.1 million ransomware attacks only in the first half of 2022, it is clear that the fast adoption of new technologies without a safety net is a huge problem.
This is where AI TRiSM comes into play. It gives organizations the power to utilize the technology more safely and securely. The framework allows for a stronger foundation by incorporating measures like data encryptions, secure data storage, multi-factor authentication, and more accurate outcomes through AI algorithms.
Making these AI tools more secure will allow companies to focus on using them for growth, improved efficiency, and better customer experience.
What are Some of the Use Cases & Real-World Examples of AI TRiSM?
Two AI TRiSM use cases that truly showcase the overall capabilities of the frameworks to drive innovation, create value, and create better outcomes for both businesses and the people are:
Fair, Transparent, and Accountable AI Algorithms
Today, companies are working towards creating fair, transparent and accountable AI models with high-level ethical standards. To achieve this, companies are regularly checking their model predictions against fairness tests and setting up a model monitoring framework. This approach makes the models ethical, while helping build trust among the customers and stakeholders.
Explainable Cause-and-Effect Relationships AI Models
AI models that generate mathematically explainable models capable of identifying cause-and-effect relationships are the future. These AI algorithms will help create models that validate results, eventually leading to several breakthroughs. The ability of these models to process large amounts of data and identify patterns and relationships in them can help organizations make better decisions.
Why Do Businesses Need AI TRiSM Ethos in AI Solutions?
Apart from the fact that AI TRiSM can be beneficial for organizations, there are several other reasons for organizations to look at TRiSM framework in their AI solutions. For one, several institutions, including educational ones, social media companies, and others, are prohibiting the use of generative AI tools like Bard and ChatGPT. Additionally, there have been concerns about their potential dangers and the lack of ethical and responsible considerations.
While there are some that see overseeing agencies for ethical and responsible AI frameworks as the solution, others are completely against AI adoption until something is done about the following concerns.
AI legislation, acts, and regulations are now also being discussed. Therefore, AI services companies need to consider the various factors while working on their AI solutions.
What is the market size of AI TRiSM solutions?
By 2032, the global AI TRiSM market is expected to rise to USD 7.4 billion as per a report by Allied Market Research Report. In this, North America has the biggest market share. The early adopters of technology include banking, healthcare, transportation, and government agencies. All these predictions make being AI services providers with AI TRiSM framework in place a lucrative business choice.
How to Introduce AI TRiSM quotient to Organizations in 2024?
Any change in the framework of how the company operates or creates will get some sort of backlash from the people. AI TRiSM is no different. It is an exceptional technology, but its adoption can take time. Here are some key practices that AI development services providers can follow to create the perfect environment for AI TRiSM:
- Create a team of professionals dedicated to AI TRiSM efforts in your AI solutions.
- Leverage robust AI solutions for security, privacy, and risk management to maximize business results.
- Utilize the expertise of diverse experts, including lawyers, data scientists, and ethicists.
- Give priority to AI explainability and interpretability
- Protect the data well using encryptions, access control, and data anonymization.
- Incorporate risk management through a focus on performance and accuracy.
Bring Your Vision to Life with AI Solutions & AI TRiSM Framework
Embracing AI TRiSM in all your AI solutions will ensure better reliability, safety, and resilience. It will also bring about more trust while managing risks and upholding security standards. If you want to navigate the ever-evolving landscape of AI solutions with confidence, get the right market. The right AI/ML company can equip you with the knowledge and tools of AI TRiSM, assisting you in implementing robust trust, risk, and security management practices in your AI initiatives.