Today we are witnessing one of history’s rare moments. It is the rise of a revolutionary technology that has the potential to fundamentally change business and society forever. That technology is, of course, artificial intelligence.
Given how AI is already helping companies achieve their goals, if we don’t act now, we risk falling behind our AI-enhanced competitors and missing out on the opportunity to meet tomorrow’s customer expectations. There is a lot of pressure. But success in applying AI, whether based on state-of-the-art machine learning (ML) or the latest generative AI leveraging underlying models, is not measured solely by speed. is not. There are several important considerations when deciding on your AI strategy.
How to create a competitive edge
The key to success lies at the heart of your business: the key activities and capabilities that underlie who you are and who you serve. Whether based on ML or based on underlying models, the more you customize your AI models to these priorities, the better you can serve your customers and deliver real business value. increase. It is imperative that the business strategy guides the data strategy, as the underlying model enables AI to be fine-tuned to enterprise-specific data and domain knowledge with a specificity never before possible. To be truly impactful, AI must be integrated into existing workflows and systems to automate key processes across areas such as customer service, supply chain, and cybersecurity.
How to extend AI across your business
A good AI is only as good as the data that drives it, and it’s important to identify the right dataset from the start. While poor data quality can stall projects, companies argue that excessive data complexity and integration challenges are major obstacles to AI adoption. .1 Q: What is the most important data? Which data gives the strongest competitive advantage? And because the data that drives business processes is often widely distributed, companies are architecture should be created. In fact, your data is everywhere: on-premises data centers, mainframes, private clouds, public clouds, edge. To successfully scale your AI efforts, all your data must be available everywhere. A hybrid cloud architecture provides the data foundation for extending AI deep into your business.
How to advance trustworthy AI
Where your business depends on delivering essential services or delivering accurate information, insights and recommendations at scale and at speed, your system should maximize availability and minimize errors. must be able to The risk and cost of reputational damage and regulatory fines can be high if the model contains bias, or if the AI model is misleading, “hallucinating” or unexplainable. AI must be explainable, fair, robust, and transparent, prioritizing the protection of consumer privacy and data rights to create trust. Data and AI lifecycle management is a key part of improving data access, enforcing governance, reducing costs, and getting high-quality models into production faster.
Three Opportunities to Make AI Practical
Here are the best opportunities for businesses to benefit from AI today:
1. Digital Labor
AI is fundamentally about making things better for people. Free employees from repetitive tasks, deliver faster results, and make better, data-driven decisions by leveraging AI across highly complex or mundane processes. We support. Higher job satisfaction leads to lower turnover, and higher employee satisfaction leads to higher customer satisfaction.
For example, Dutch bank ABN AMRO worked with IBM Consulting to build a conversational assistant based on IBM Watson Assistant software to deploy customer service agents answering 90% of customer requests in English or Dutch in 2021.
2. IT automation
A more automated information infrastructure greatly enhances the oversight capabilities of IT teams, enabling them to achieve new levels of resilience and efficiency. As a result, you can spend your time and expertise more productively to develop new innovations and bring products to market faster.
For example, as the applications that run your business become more complex, AI can help you make optimization decisions, matching application performance demands with infrastructure supply.
By using IBM Turbonomic, Carhartt increased the efficiency of its cloud environment by 45%.
3. Security and Compliance
Cyberattacks are more prevalent, creative and faster than ever. AI can not only expand visibility and reduce response times through orchestration and automation, but it can also build compliance and security controls into his hybrid cloud architecture. It determines who has access to what and when, and helps automate compliance controls for the ever-expanding set of regulations that companies must comply with.
For example, AI and automation can reduce incident response time from days and hours to minutes, closing the gap to attackers. It also helps validate user access, discover exposed assets, and enforce compliance measures. And with the multitude of security tools most businesses need to manage, AI can be used to create a unified workflow. With QRadar, TalkTalk stopped potential threats on average 8x faster.
Let’s harness AI to make the world work better together. See how IBM can help you harness AI to find business benefits.
This post was created by IBM and Insider Studios.
1IBM Global AI Adoption Index 2022, IBM.com
