AI in Business

AI Blog · AI in Business

How is AI being applied to business?

Artificial Intelligence (AI) is still an unfolding technology, and its complete influence and advantages remain untapped. AI breakthroughs are among various elements causing disruption in current markets and facilitating fresh digital business projects. Moreover, AI finds applications in diverse sectors, companies, and roles in myriad ways.

Here are a few examples of AI application in business operations:

1. AI in Human-like Communications: Machine learning (ML) is paving the way for AI applications such as chatbots, autonomous vehicles, and smart robots that replicate human communications.

2. AI in Biometrics: Through deep learning techniques, AI provides solutions like facial recognition and voice recognition. Neural networks are used to hyper-personalize content through data mining and pattern recognition.

3. AI in IT Operations/Service Desk: AI facilitates IT support with Virtual Support Agents (VSAs), ticket routing, information extraction from knowledge management sources, and providing answers to common questions.

4. AI in Supply Chain Management: AI assists with predictive maintenance, risk management, procurement, order fulfillment, supply chain planning, promotion management, and decision-making automation.

5. AI in Sales Enablement: AI can help identify new leads, nurture prospects through intelligent tracking and messaging, and improve sales execution and revenue through guided selling.

6. AI in Marketing: AI enables real-time personalization, content and media optimization, campaign orchestration, and uncovers new customer insights for effective marketing deployment.

7. AI in Customer Service: AI predicts customer needs and proactively deflects inquiries. Virtual customer assistants (VCAs) equipped with speech recognition, sentiment analysis, and automated quality assurance provide round-the-clock customer service.

8. AI in Human Resources: AI facilitates recruitment processes, skills matching, and leverages recommendation engines for learning content, mentors, career paths, and adaptive learning.

9. AI in Finance: AI helps in dynamic processes requiring judgment and handling unstructured, volatile, high-velocity data. Examples include new accounting standards compliance, expense reports review, and vendor invoice processing.

10. AI in Sourcing, Procurement, and Vendor Management (SPVM): AI assists in spend classification, contract analytics, risk management, candidate matching, sourcing automation, virtual purchasing assistance, and voice recognition.

11. AI in Legal: AI finds use in contract assembly, negotiation, due diligence, risk scoring, life cycle management, e-discovery, invoice classification, and more.

As enterprises adopt AI more widely, it’s inevitable that accompanying threats will arise, potentially posing significant risks to the organization. It’s crucial that these threats are assessed proactively to bolster stakeholder confidence in AI.

By 2025, it’s anticipated that regulations will demand greater emphasis on AI ethics, transparency, and privacy. Far from inhibiting AI, these requirements will likely foster trust, stimulate growth, and enhance the global performance of AI.