Role of AI in Business Decision-Making
Artificial Intelligence is becoming a key component in numerous technological
advancements. Whether it’s Meta, ChatGPT, virtual assistants, or reinforcement learning,
AI solutions are becoming integral to industries. AI is helping enterprises improve their
decision-making by automating data analysis, providing insights, and identifying
patterns that are primarily difficult for humans to spot. Businesses can anticipate market
shifts, optimize operations, and manage risk, leading to strategic planning and achieving
competitive advantage. Here’s how AI is improving decision-making:
The Risks of Trusting Unverified AI
With most changes in the digital space driven by AI, trust becomes critical. Although AI
has immense potential to enhance productivity and decision-making and drive
innovation, trusting unverified AI can cause severe damage across various domains.
Leveraging unverified AI models without thorough fact-checking may generate
inaccurate and misleading information. This can influence public opinion, academic
work, and even policy decisions.
Secondly, if AI systems are trained on biased data, they can perpetuate or exacerbate
existing inequalities. Without any audit, AI can probably discriminate based on
demographics or gender and reinforce harmful stereotypes in image or language
generation. Just imagine what unfair decisions in the legal or healthcare industry can
result in. Trusting unverified AI can open an attack surface for deepfakes and spoofed
content to deceive users. AI models that are not tested can be hacked or manipulated,
resulting in dangerous outputs.
The Risks of Trusting Unverified AI
With most changes in the digital space driven by AI, trust becomes critical. Although AI
has immense potential to enhance productivity and decision-making and drive
innovation, trusting unverified AI can cause severe damage across various domains.
Leveraging unverified AI models without thorough fact-checking may generate
inaccurate and misleading information. This can influence public opinion, academic
work, and even policy decisions.
Secondly, if AI systems are trained on biased data, they can perpetuate or exacerbate
existing inequalities. Without any audit, AI can probably discriminate based on
demographics or gender and reinforce harmful stereotypes in image or language
generation. Just imagine what unfair decisions in the legal or healthcare industry can
result in. Trusting unverified AI can open an attack surface for deepfakes and spoofed
content to deceive users. AI models that are not tested can be hacked or manipulated,
resulting in dangerous outputs.
Manjeet Kumar
VP, Delivery Quality Engineering
Manjeet Kumar, Vice President at Tx, is a results-driven leader with 19 years of experience in Quality Engineering. Prior to Tx, Manjeet worked with leading brands like HCL Technologies and BirlaSoft. He ensures clients receive best-in-class QA services by optimizing testing strategies, enhancing efficiency, and driving innovation. His passion for building high-performing teams and delivering value-driven solutions empowers businesses to achieve excellence in the evolving digital landscape.
