{"id":4174,"date":"2024-08-30T21:14:53","date_gmt":"2024-08-30T21:14:53","guid":{"rendered":"https:\/\/solutionsreview.com\/marketing-automation\/?p=4174"},"modified":"2024-09-30T16:30:25","modified_gmt":"2024-09-30T16:30:25","slug":"the-top-questions-for-tech-leaders-to-ask-when-selecting-an-ai-solution","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/marketing-automation\/the-top-questions-for-tech-leaders-to-ask-when-selecting-an-ai-solution\/","title":{"rendered":"The Top Questions for Tech Leaders to Ask When Selecting an AI Solution"},"content":{"rendered":"

Brett Weigl, the SVP of Product Management for AI at Genesys<\/a>, shares a few questions that tech leaders should ask when researching and selecting an AI solution. This article originally appeared in\u00a0Insight Jam<\/a>, an enterprise IT community that enables human conversation on AI.<\/span><\/strong><\/em><\/p>\n

\"\"<\/a>Choosing the right artificial intelligence (AI) solution for your organization is a critical decision that can significantly influence operational efficiency and customer satisfaction. Thousands of AI companies worldwide are marketing hundreds of AI-driven products\u2014each with a different purpose and use case. In this vast sea of AI options, it can often feel like it\u2019s sink or swim to drive actual return from such a huge investment. As tech leaders face mounting pressure to increase profitability, using AI effectively can be the differentiator on which business is gained or lost. <\/span><\/p>\n

A 2024 Genesys study confirmed this urgency, with more than 50 percent of customer experience (CX) leaders agreeing that adopting AI is the key to improving customer loyalty, boosting financial outcomes, and outpacing the competition in the next five years.\u00a0<\/span><\/p>\n

Today, AI is forging new opportunities for brands to connect with customers. Organizations can offer instant, 24\/7 support tailored to each person\u2019s needs and resolve common issues without human intervention. Powered by sophisticated natural language processing, virtual assistants can engage customers in friendly conversational interactions that mimic the familiarity of a real employee. AI-driven analytics enable companies to analyze vast amounts of customer data<\/a>, uncovering insights into their preferences, behaviors, and pain points. AI copilots that surface knowledge and automate tasks allow human agents to resolve complex and high-value customer inquiries more efficiently and quickly. \u00a0<\/span>\u00a0<\/span><\/p>\n

A well-chosen AI solution can scale with the business by supporting growth and adapting to changing needs. However, AI products have stark differences, especially concerning data integrity, privacy, and ethics. To unlock AI’s full potential, tech leaders need a secure, unified platform that’s easy to deploy and allows them to innovate and tailor features for their customers’ needs. <\/span>\u00a0<\/span><\/p>\n

When investing in AI, here are four essential criteria brands should evaluate to make a strategic and intelligent decision:<\/span>\u00a0<\/span><\/p>\n

Is it secure? \u00a0<\/strong><\/span>\u00a0<\/strong><\/span><\/h3>\n

According to a Genesys study, 64 percent of CX leaders are concerned that data privacy and security will be their top obstacle when adopting more AI-based solutions. Furthermore, 75 percent worry that trust and privacy issues may prevent their business from making future AI investments.<\/span>\u00a0<\/span><\/p>\n

Protecting data integrity is paramount to a secure AI solution. Native AI that is purpose-built into a platform speeds up time to value for businesses. It is also a fundamental attribute that helps organizations adhere to strict AI and data ethics requirements, offering the best way to safeguard data and ensure ownership rights are respected.<\/span>\u00a0<\/span><\/p>\n

When AI services depend on complex, multi-vendor integrations, it\u2019s harder to guarantee customer data security. This could result in data being used without proper consent, unauthorized data access, and potential exploitation of sensitive information. It\u2019s also important to review service agreements thoroughly to ensure data is only used as you expect it to be used.<\/span>\u00a0<\/span><\/p>\n

In a secure AI solution, training data is carefully vetted. Whether it comes from customers under a data-sharing agreement with consent or another source, this vetting process builds trust, adheres to data privacy regulations, and retains data ownership. All data should be anonymized, stripping away personally identifiable information to safeguard organizational privacy. Human data validation ensures accuracy and reduces the risk of biases and errors that could affect the AI’s performance. Additionally, every AI model should undergo rigorous testing to verify its results. This comprehensive approach prevents data misuse and enhances an AI solution’s quality and trustworthiness.<\/span>\u00a0<\/span><\/p>\n

Is it compliant? \u00a0<\/strong><\/span>\u00a0<\/strong><\/span><\/h3>\n

Non-compliant AI poses significant risks to businesses. In a non-compliant solution, an organization’s data can exist outside of allowed geographic jurisdictions, which can violate data privacy laws. Companies can face legal repercussions and reputational damage if data operations do not abide by national, local, or global regulations. <\/span>A responsible AI solution should ensure compliance by obtaining and heeding global and regional compliance regulations and certifications.\u00a0<\/span>\u00a0<\/span><\/p>\n

Two new EU regulations that impact AI are making headlines: the Digital Operational Resilience Act (DORA), which will take effect in 2025, and the Artificial Intelligence Act (AI Act), which passed in May 2024. Although they are now limited to companies doing business in the EU, these regulations will likely be a model for future AI regulations worldwide. \u00a0<\/span>\u00a0<\/span><\/p>\n

DORA and the AI Act are descendants of similar compliance laws like the General Data Protection Regulation, FedRAMP, and others, which exist to protect fundamental data rights and provide cloud security. Adherence to these regulations demonstrates an organization\u2019s commitment to data security and privacy. These certifications also build customer trust, mitigate risks, and give companies a competitive edge. <\/span>\u00a0<\/span><\/p>\n

Is it contextual?<\/strong><\/span>\u00a0<\/strong><\/span><\/h3>\n

AI that is purpose-built and deeply embedded across an entire platform is integral for addressing customer and employee needs. Working in unison, an end-to-end architecture of conversational, predictive, and generative AI capabilities allows it to continuously learn for smarter outcomes, better results, and clearer context. With this type of iterative learning process, an AI\u2019s responses are highly informed and aligned with specific actions being performed at any moment to provide the most personalized and empathetic outcome.<\/span>\u00a0<\/span><\/p>\n

Driven by AI, contextual experiences show consumers that their wants and needs matter to a business. This means virtual and human agents already know a customer\u2019s name and information regardless of their contact method. Companies can anticipate customers’ needs, understand their preferences, and resolve issues effectively at the first point of contact and on the channel of a customer\u2019s choice. <\/span>\u00a0<\/span><\/p>\n

AI without context and journey awareness creates frustration and disconnected experiences and erodes operational efficiency. When disparate AI solutions are leveraged to solve multiple needs, broken customer journeys will follow. This ultimately results in unsatisfactory experiences where historical information about the customer is not carried forward, and customer intent and preferences are not understood. Lack of context further extends to the employee experience, forcing agents to spend additional time and effort to respond accurately and appropriately.<\/span>\u00a0<\/span><\/p>\n

Is it effortless?<\/strong><\/span>\u00a0<\/strong><\/span><\/h3>\n

AI that allows organizations to achieve impactful results is deployed effortlessly and guides customers through building, implementing, and optimizing it out of the box. Customers can also be self-sufficient, minimizing IT involvement in day-to-day maintenance and support.<\/span>\u00a0<\/span><\/p>\n

Effortless AI solutions are turnkey and ready to use from day one. A single, unified platform with built-in AI does not require skilled resources or data scientists and is more accessible to organizations of all sizes and with technical proficiencies. Companies can quickly reap the rewards of their AI investment without the prolonged wait typically associated with complex integrations, enabling faster time to value.<\/span>\u00a0<\/span><\/p>\n

Harnessing the Power of Your AI solutions<\/strong><\/span>\u00a0<\/strong><\/span><\/h3>\n

Not all AI is created equal, and tech leaders must be vigilant when selecting an AI solution. When chosen correctly, AI products can transform your business into a digital powerhouse by elevating employee effectiveness and customer satisfaction. By focusing on these essential criteria, organizations everywhere can harness AI to drive innovation and consumer loyalty.<\/span><\/p>\n

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<\/a><\/p>\n<\/div>\n\t\t<\/div><\/div><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Brett Weigl, the SVP of Product Management for AI at Genesys, shares a few questions that tech leaders should ask when researching and selecting an AI solution. This article originally appeared in\u00a0Insight Jam, an enterprise IT community that enables human conversation on AI. 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