Implementing AI: The benefits, uses cases and measuring value

How Small Businesses Can Use AI Tools

From enhancing operational efficiency to revolutionizing customer experiences, AI offers immense potential. Creating a robust AI policy is imperative for companies to address the ethical, legal and operational challenges that come with AI implementation. Companies are using AI to improve many aspects of talent management, from streamlining the hiring process to rooting out bias in corporate communications. Moreover, AI-enabled processes not only save companies in hiring costs but also can affect workforce productivity by successfully sourcing, screening and identifying top-tier candidates. As natural language processing tools have improved, companies are also using chatbots to provide job candidates with a personalized experience and to mentor employees.

“This discrepancy between recognizing AI’s importance and taking concrete steps to adopt it could stem from AI’s status as an emerging technology. But a more likely explanation is a lack of trust and understanding regarding its capabilities and limitations,” says Catherine Wilks, senior director at business transformation consultancy Slalom. The process of creating a future-ready team with AI is not only about technical integration but also requires an investment in skills and values that will ensure harmony and effectiveness between humans working alongside intelligent systems. First, creating an environment of transparency and education is important so that the employees understand all its advantages along with removing misconceptions. To offset this resistance, experts say, banks should focus on data transparency, customer autonomy and brand trustworthiness. This means giving customers a say in how their data is handled and being more open and honest about the bank’s AI plans, intent and data strategy.

Students and others quickly criticized the technology’s use in such circumstances, leading the university to apologize for “poor judgement.” Bad actors are using AI to increase the sophistication of their attacks, make their attacks more effective and improve the likelihood of their attacks successfully penetrating their victims’ defenses. The poster bot for this type of risk is the infamous Tay, released by Microsoft on Twitter back in 2016. Engineers had designed the bot to engage in online interactions and then learn patterns of language so that she — yes, Tay was designed to mimic the speech of a female teenager — would sound natural on the internet. Sheffi said such technology-driven changes in the labor market in the past have led to labor unrest and could possibly do so again. Organizations might then need to adjust their AI roadmaps, curtail their planned implementations or even eliminate some of their AI uses if they run afoul of any forthcoming legislation, Kelly said.

AI can also transcribe and translate language and generate code, providing businesses with quicker, easier, and more cost-effective access to these specialized skill sets. Once an understanding of what AI does well is gained, leaders can consider the challenges that their business is facing. A strong use case is built on the alignment of technological capabilities and genuine organisational needs. After all, leaders don’t want to end up with a “solution in search of a problem”.

AI For Consumer-Based Businesses

In addition, there are ongoing expenses related to talent acquisition, technology upgrades, and maintenance. The accuracy and effectiveness of generative AI systems hinge on access to extensive datasets, which could include sensitive information. Make sure you prioritize data protection, enforce strict cybersecurity measures, and follow industry regulations. By delivering data-driven insights and predictive modeling as well as automating complex data analyses, generative AI enhances the decision-making process. GenAI uncovers underlying patterns and trends and offers reliable forecasting, enabling you to make better business decisions. Businesses can apply generative AI for hyper-personalized recommendations and faster resolutions from chatbots, elevating the customer experience and engagement.

This helps teams work smarter and spot opportunities faster than manual analysis allows. AI also streamlines workflows by connecting systems and surfacing relevant information quickly. For example, AI-powered project management tools can automatically assign tasks, track progress, and flag potential delays. It can take care of boring tasks so people can focus on more important jobs.

GenAI in Marketing and Media

To maximize the effectiveness of any AI tool, it can be helpful to think of it like any other process or technology being introduced to the business. Additionally, the CAIO should engage with the chief diversity officer to involve diverse talents with the deployment of new AI systems. It’s essential to minimize the risk of bias and discrimination being embedded within these systems and make sure that everyone in the organization has an opportunity to participate equitably in driving innovation. This is where the chief people officer comes in, fostering excitement about change, engaging talent with the transformation strategy and organizing critical training that will equip people with the skills they’ll need. They can also give insights into how the new technologies will affect workplace culture. Exec teams often see a chief AI officer as the solution to their AI implementation challenges.

• Having an orchestration layer that can move applications between providers without impacting the business, is therefore critical for building agility into AI business offerings and processes.
• However, this rapid adoption brings significant risks, particularly with the rise of “Bring Your Own AI.” A striking 78% of AI users are bringing their own AI tools to work, often without organizational guidance.
• For the finance sector, generative AI technologies support decision-making and bolster security through automating complex processes.

According to the study, customer agents who used AI were able to handle 13.8 percent more customer inquiries per hour, and professionals who used AI could write 59 percent more business documents per hour. Learn how the integration of AI and machine learning into manufacturing processes can help organizations meet quality control needs, such as defect detection and waste reduction. Many manufacturers are eager to implement AI quickly to take advantage of potential benefits and improve the organization’s competitive advantage. Unfortunately, doing too much too soon can result in a poor implementation that doesn’t deliver ideal results. AI manufacturing systems must integrate with other tech to improve manufacturing processes.

Consider, for example, what would happen if workers don’t trust an AI solution on a factory floor that determines a machine must be shut down for maintenance. Even if the AI system is nearly always accurate, if the user doesn’t trust the results it produces then that AI system is a failure. The main takeaways underscore the importance of aligning AI initiatives with your business strategies, to make sure that resources are allocated efficiently, and opportunities are not missed. Lastly, consultancies can articulate a unique value proposition for AI initiatives, which can help your company differentiate your brand in the saturated market. On the other hand, if you fail to do so, your efforts could result in quality compromises, security vulnerabilities, and stakeholder mistrust. Rushing AI deployment can lead to quality compromises, security vulnerabilities, and operational disruptions.

Vendors of AI PCs typically include a CPU, a GPU and a neural processing unit — a dedicated hardware component for AI acceleration. Moreover, unregulated AI applications can result in errors or biased outcomes, which may harm a business’s reputation and lead to legal complications. The risks extend beyond data breaches to include potential intellectual property violations and inconsistent decision-making across the organization. Ungoverned AI use also poses substantial risks, particularly with BYOAI practices. Employees using AI tools for work tasks without guidelines can inadvertently compromise data privacy and security. Without proper oversight, organizations face threats from AI applications accessing sensitive information or producing unreliable outputs.

Watson Health uses big data to analyze a massive volume of medical literature, patient records and clinical trial information for healthcare professionals to make informed decisions faster, advance research quickly and personalize treatment plans. The success of Watson Health is a testament to the revolutionary nature of AI in healthcare, which enhances patient outcomes and advances medical knowledge. “Customers are more likely to share their data when they understand how that data will be used, why sharing it is important and how it will ultimately benefit them,” notes the Deloitte report. For AI to have the greatest impact on your business, you want to strategically choose and deploy tools in areas that make the most sense.

Implementing AI throughout our business

This involves evaluating data requirements, infrastructure needs, and potential use cases. Here’s what you need to know to effectively transform and grow your organization while protecting against risks and responding to rapid changes. Enterprise use cases for generative AI include everything from writing marketing copy to discovering new pharmaceuticals. Many people are currently ChatGPT concerned about how AI will affect their livelihoods. Workers who think AI will take away their jobs had a 27% lower intent to stay at their company, according to a 2023 Gartner survey. This should encompass how it aligns with the company’s goals, resonates with its values, how it’s being used in the workplace, and how it’ll benefit and support employees within their roles.

The implementation of RankBrain — an AI system that helped to enhance search results relevance by interpreting user queries and providing more appropriate answers has definitely made a huge difference in the way we do web searches. This not only improved the user experience but also cemented Google’s position as a leader in technology. Not only does the use of machine learning algorithms and natural language processing facilitate workflow, but it also enhances human performance, creating a complementary synergy. Additionally, AI supports predictive analytics, allowing firms to forecast trends and prevent risks while making decisions. AI tools can also enable predictive analytics, providing valuable insights to decision makers based on current and historical data.

I have witnessed many businesses often underestimate the evolutionary pace of AI and its long-term impact across various sectors. When navigating the complexities of AI implementation, partnering with seasoned professionals can significantly streamline the process and maximize the value of your investment. So here are a few tips on how to efficiently integrate AI into your business operations while optimizing costs. If you are still not convinced, here are some advantages of implementing AI in your business.

• The adoption of shadow AI — the unauthorized use of AI tools at work — is another risk enterprises must address.
• This guide to enterprise AI provides the building blocks for becoming successful AI implementers, users and innovators.
• Leo Rajapakse is the Head of Platform Infrastructure & Advanced Technology for Grupo Bimbo.
• Younger generations’ optimism about AI also dovetails with the importance of DEX.

Remember, an effective AI policy is a living document that evolves with technological advancements and societal expectations. By investing in responsible AI practices today, businesses can pave the way for a sustainable and ethical ChatGPT App future tomorrow. Beyond automating repetitive tasks like customer service chatbots and robotic process automation (RPA) for administrative tasks, AI enhances critical decision-making by providing deeper insights into data.

If AI systems are used to manage safety-critical processes, companies should ensure transparency, auditing mechanisms and human oversight are in place to mitigate potential risks. You can foun additiona information about ai customer service and artificial intelligence and NLP. Emerging trends and advancements in AI tools hold many promising applications for small businesses. The ability to increasingly personalize customer experiences by capitalizing on historical data, for instance, can offer small businesses a competitive edge. Employees should undergo meaningful training to understand the legal and ethical concerns surrounding AI, and regular audits should be conducted to identify any concerns over non-compliance, with a focus on deterring bias and discrimination. There is also a growing call for AI systems to be more transparent, with all stakeholders having a clear understanding of how the tools are making decisions. When companies implement more explainable AI technologies from the start, it can help to address this concern.

It expedites product development, keeps their quality in check, and predicts equipment features, improving the way manufacturers approach production and maintenance. Some of the most popular GenAI tools for manufacturing include Altair, Autodesk, and Pecan AI. For the finance sector, generative AI technologies support decision-making and bolster security through automating complex processes. GenAI use cases in this field include gathering market insights, making budget predictions, and detecting fraud to safeguard financial operations. Some of the most popular GenAI tools for finance and risk management include Datarails, AlphaSense, and Stampli.

Explore our AI services platform that allows for purpose-built AI assets and models and role-based generative AI assistants. IBM offers AI solutions to help you build the future of your business today. Including IBM watsonx, the data and AI platform comes with a set of AI assistants. The deep scientific expertise of IBM Research® and the teams of expert consultants are ready to help you scale responsible AI across the enterprise.

How to Implement AI — Responsibly

As AI augments routine business processes and becomes part of a business’ day-to-day operations, a strong change management strategy might be necessary as roles shift across an organization. During the organizational phase, business leaders also determine who owns the data, the data security measures in place, and the conditions for using the data. This process creates a self-service pipeline making data accessible to the right people at the right time. Leo Rajapakse is the Head of Platform Infrastructure & Advanced Technology for Grupo Bimbo. He leads the company’s Technology Platform organization, which provides critical technology infrastructure platforms on-premise and cloud. Before joining Bimbo Bakeries, Leo held several leadership positions with the technology arms of leading institutions, including the Australian Government.

AI integration involves incorporating artificial intelligence tools and technologies into business processes. This requires understanding key AI concepts and developing strategic implementation approaches. As generative AI continues to make waves in various industries, top companies are maximizing its potential to revamp their products and services. From personalized content recommendations to better fraud detection, more and more organizations are integrating the technology into their operations.

AI Challenges & Predictions

In fact, over 50% of US companies with more than 5,000 employees currently use AI. The United Arab Emirates is the next largest, with 58% of companies using AI, followed by Singapore at 53%. Over the last five years, AI usage has flattened out and stabilized after rapid growth from 2017 to 2018. That means that over 82% of companies are either using or exploring the use of AI. For employees concerned about their future in an AI-driven workplace, Chotima advocates developing the “fusion skills” to effectively work alongside AI.

Teams also need to monitor feedback and resistance to an AI deployment from employees, customers and partners. Qualitative metrics, such as enhanced product quality and innovation, should also be considered. Recognize that the path to AI starts with understanding the data and good old-fashioned rearview mirror reporting to establish a baseline of understanding.

Building AI expertise is essential for your long-term success and sustainability. While hiring and training AI talent may require an initial investment, it can yield significant returns in terms of innovation, efficiency, and competitive advantage. By aligning AI initiatives with your strategic goals and focusing on areas with the highest potential for improvement, you can ensure that your investment delivers measurable results that directly contribute to your business’s success. In my opinion, this gap between current AI utilization and its potential presents both a challenge and an opportunity for businesses.

For example, Samsung’s Galaxy S24 Ultra has AI built into the phone in the form of a transcript assistant, “circle to search” feature, and real-time translation capabilities. There is much concern over worker displacement due to implementing ai in business the use of AI technology. Massachusetts Institute of Technology (MIT) economists Daron Acemoglu, David Autor, and Simon Johnson have written about how digital technologies have exacerbated inequality over the past 40 years.

Paul Maplesden creates comprehensive guides on business, finance and technology topics, with expertise in supply chain and SaaS platforms. There are plenty of free crash courses and bootcamps that offer remote training programs which will cover the basics of AI and equip employees with the skills and experience needed. While a certificate itself won’t make employees more trusting of AI, recognition of their achievement could help them to see the benefits of AI skills in the workplace. Finally, a systematic and collaborative approach to addressing challenges ensures that AI adoption is done in the right way. An ethical committee can set regular deadlines to audit, train and evaluate AI models so that the insights these models produce are trustworthy and valuable to the business.

Only 23% of businesses in the UK have reported wanting to experiment and take risks with AI to maximize its benefits. Striking up partnerships with AI experts and reskilling or upskilling existing employees can help companies overcome this challenge. In fact, almost half of the companies surveyed by McKinsey have taken this approach. Knowledge of AI isn’t just essential for a successful implementation—it’s key to using the technology effectively. Other channels that can help in sourcing AI talent and bridging the skills gap include top-tier technical universities, global technology companies, industry organizations, training academies, and diversity-focused programs. Amid rising financial pressure and increasing consumer expectations, business leaders across all industries are turning to AI as the silver bullet to drive greater efficiency, reduce costs, and secure a competitive advantage.

We enhance the impact of AI development and cloud technologies in business transformation, working across an open ecosystem of partners to deliver any AI model on any cloud. AI projects can involve various highly skilled professionals, including data engineers, data scientists and data analysts. Some organizations might decide to improve existing employees’ skillsets, while others might need to hire significant new talent to help ensure a smooth and responsible AI transformation. This can involve labor from human resources departments, or carefully managed transition programs. With the foundation of a strong automation and intelligent application practice, organizations can build AI more deeply into their business and transform how the company works.

This is large-scale change for leaders to manage, if they want to actually be innovation-first and AI-enabled. Any innovation involves trying new things, but with AI, there are multiple types of risks. Firstly, the technology is evolving extremely rapidly – which means the risk of obsolescence is high, and skills can be hard to acquire. The proliferation of platforms and tools can also create a risk of suboptimal choice making. Because there are so many options for business leaders to choose from, it can be hard to know which is right for your organization. IBM’s AI consulting services bring together deep industry experience, along with AI technology, that augments rather than replaces your team.

However, using it to tick the AI box in your organization is not necessarily the answer – at least not the most effective, safe, and impactful one. As companies look to cut costs and increase outputs, business spending on AI tools and overall AI adoption will likely continue to grow. Designed for business owners, CO— is a site that connects like minds and delivers actionable insights for next-level growth. Chamber of Commerce’s Chamber Technology Engagement Center (C_TEC) report sheds light on the influence of technology on small businesses nationwide. Our best expert advice on how to grow your business — from attracting new customers to keeping existing customers happy and having the capital to do it.

While this generative AI tool is excellent at producing SEO-friendly content, Jasper AI occasionally writes generic output that is inaccurate, requiring human intervention and fact checking. GenAI systems can analyze customer behavior and preferences based on historical data and provide appropriate recommendations. A survey conducted by Salesforce found that 70 percent of companies using generative AI in their customer service operations reported higher customer satisfaction scores. Generative AI is a set of AI technologies that create original content—such as text, images, video, audio or software code—in response to a user’s prompt or request. In consumer-facing applications, generative AI can create personalized content in real-time.