What Makes a Company Successful at Using AI?

With continued advancements, AI is quickly becoming a precious resource for companies across industries. To better understand how businesses use AI, Forbes Advisor surveyed 600 business owners using or planning to incorporate AI in business. The results revealed AI’s impact on areas such as cybersecurity, fraud management, content production and customer support, including the use of top chatbots. The goal of AI is to either optimize, automate, or offer decision support. AI is meant to bring cost reductions, productivity gains and in some cases even pave the way for new products and revenue channels.

But while machine learning has many applications, it is just one of many AI-related technologies capable of solving business problems. For example, the AI techniques implemented to improve customer-call-center performance could be very different from the technology used to identify credit-card-payments fraud. It’s critical to look for the right tool to solve each value-creating business problem at a particular stage in an organization’s digital and AI journey. No AI model, be it a statistical machine learning model or a natural language processing model, will be perfect on day one of deployment.

Will robotic process automation, or a cheaper, non-AI process deliver the same outcome?

Applying this ethos to the way we use AI is the surest way to unlock unprecedented opportunities. Businesses will need to navigate the evolving landscape of this powerful technology and ensure its ethical and efficient use. The winter 2024 issue features a special report on sustainability, and provides insights on developing leadership skills, recognizing and addressing caste discrimination, and engaging in strategic planning and execution. Recently, like millions of people, I used a ride-sharing app on my smartphone.

For example, companies may choose to start with using AI as a chatbot application answering frequently asked customer support questions. In this case, the initial objective for the AI-powered chatbot could be to improve the productivity of customer support

agents by freeing up their time to answer complex questions. A milestone would be a checkpoint at the end of a proof-of-concept (PoC) period to measure how many questions the chatbot is able to answer accurately in that timeframe. Once the quality

of AI is established, it can be expanded to other use cases. Defining milestones for an AI project upfront will help you determine the level of completion or maturity in your AI implementation journey. The milestones should be in line with the expected return on investment and business outcomes.

steps to AI implementation

We found that industries leading in AI adoption—such as high tech, telecom, and automotive—are also the ones that are the most digitized. Likewise, within any industry, the companies that are early adopters of AI have already invested in digital capabilities, including cloud infrastructure and big data. In fact, it appears that companies can’t easily leapfrog to AI without digital-transformation experience.

Once you have chosen the right AI solution and collected the data, it’s time to train your AI model. This involves providing the model with a large, comprehensive dataset so the model can learn patterns and make informed predictions. A steering committee vested in the outcome and representing the firm’s primary functional areas should be established, she added. Instituting organizational change management techniques to encourage data literacy and trust among stakeholders can go a long way toward overcoming human challenges. « The harder challenges are the human ones, which has always been the case with technology, » Wand said. According to John Carey, managing director at business management consultancy AArete, « artificial intelligence encompasses many things. And there’s a lot of hyperbole and, in some cases, exaggeration about how intelligent it really is. »

Build a Winning AI Strategy for Your Business

Katherine Haan, MBA is a former financial advisor-turned-writer and business coach. When she’s not trying out the latest tech or travel blogging with her family, you can find her curling up with a good novel. To get the best possible experience please use the latest version of Chrome, Firefox, Safari, or Microsoft Edge to view this website. The first human received an implant from @Neuralink yesterday and is recovering well.Initial results show promising neuron spike detection. « My ongoing challenge as a data leader is to set the possibilities for these technologies without saying you can have it now — because, of course, everybody wants AI now, » he says.

Two brains are better than one, and in the case of AI, multiple brains are even better. That’s why it’s important for businesses to adopt not one but multiple LLMs, which are the backbones of generative AI. Once you’ve integrated the AI model, you’ll need to regularly monitor its performance to ensure it is working correctly and delivering expected outcomes. Early implementation of AI isn’t necessarily a perfect science and might need to be experimental at first — beginning with a hypothesis, followed by testing and measuring results. Early ideas will likely be flawed, so an exploratory approach to deploying AI that’s taken incrementally is likely to produce better results than a big bang approach. It’s hard to deny, AI is the future of business — and sooner or later, the majority of companies will have to implement it to stay competitive.

Bring overall AI capabilities to maturity

One such concern is the potential impact of AI on website traffic from search engines. According to the survey, 24% of respondents worry AI might affect their business’s visibility on search engines. The consultancy’s annual poll of data leaders suggests many organizations are suffering from an « AI-induced paralysis », where only 5% of businesses boast a high level of AI maturity, established AI departments, or clear AI processes. Stakeholders with nefarious goals can strategically supply malicious input to AI models, compromising their output in potentially dangerous ways.

• Automation is another excellent benefit of AI technology because it can complete tasks in a fraction of the time that usually takes humans.
• Lastly, nearly 80% of the AI projects typically don’t scale beyond a PoC or lab environment.
• When employees feel that AI can help enhance their performance and increase their job satisfaction, they will be more likely to embrace the technology and support the cultural transformation needed for AI’s success.
• Among the potential benefits, 74% of respondents anticipate ChatGPT assisting in generating responses to customers through chatbots.

Depending on the use case, varying degrees of accuracy and precision will be needed, sometimes as dictated by regulation. Understanding the threshold performance level required to add value is an important step in considering an AI initiative. Emphasizing efficiency in virtual workspaces needs to go beyond tidying up a desktop, and embrace both intuitive data systems and the right collaboration tools. After three decades of working with CEOs, I’ve come to find that these five fundamental habits are shared by the most successful leaders.

The data proves AI has a role in business

Once you build a shortlist, feel free to invite these vendors (via an RFI or another process)

to propose solutions to meet your business challenges. Based on the how to implement ai in your business feedback, you can begin evaluating and prioritizing your vendor list. Collect feedback, monitor performance metrics, and adjust your approach as necessary.