Gen AI beneficiaries

Forrester defines Generative Artificial Intelligence (AI) as “A set of technologies and techniques that leverage massive corpuses of data, including large language models, to generate new content (e.g., text, video, images, audio, code). Inputs may be natural language prompts or other non-code and non-traditional inputs.” 

Adoption of generative AI models among industry professionals has been varied. The versatility of Gen AI solutions, including Large Language Models (LLMs) has made them popular among professional creatives. Other groups are also leveraging the power of AI applications to streamline their workloads. 

The beneficiaries of Gen AI technology include:

• Marketers who save time by having Gen AI create a first draft. 

• Designers who mock up visual ideas from a text prompt. 

• IT staff who automate cloud configurations and find cost savings. 

• Programmers who ask Gen AI to write out complex code. 

• Data scientists who produce and share synthetic data that protects the personal information of customers. 

• Sales representatives who personalize outreach. 

• Operations specialists who share knowledge by automating meeting notes and product help Q&A. 

Gen AI risks

According to Forrester, Gen AI’s relatively short tenure poses certain risks and therefore requires certain boundaries. Like many new technologies, AI generates both customer obsession and poses serious ethical implications.

Some of the risks of Generative AI are associated with intellectual property rights (including copyright infringement) and personal data protection. One of the issues raised most frequently is also the quality of the data used to train the AI models.

Concerns have also arisen around whether Gen AI systems are meant to enhance and not replace employees or business processes. Many organizations adopt a cautious approach, where they use Gen AI for low-risk internal use cases before exposing Gen AI to external customers or mission-critical applications. 

Forrester notes that “Generative AI is very much still in its Wild West days, so it’s best to proceed with caution.” Forrester goes on to recommend “... it’s a best practice to always weigh worst case scenarios—in what ways could generative AI lead to harmful results?”

Need for responsible AI

Professionals and industry leaders, aware of the critical importance of effective risk management, have consistently advocated for responsible AI.

AI developers and users alike have called for the deployment of artificial intelligence systems in a manner that prioritizes ethical considerations, accountability, and the well-being of society. Their key concerns include:

1. Accountability and transparency: Clear accountability for AI decisions. This includes the ability to understand and explain where the outcomes come from.

2. Privacy and security: Protecting personal data and ensuring AI systems are secure from malicious attacks and misuse.

3. Human oversight: Maintaining human oversight, ensuring AI complements rather than replaces human judgment.

4. Ethical standards: Ensuring Gen AI systems align with ethical principles, such as fairness, transparency, and human rights.

Responsible AI aims to harness the benefits of AI while minimizing potential harms, fostering trust, and ensuring that AI advancements contribute positively to society.

Work with a data expert

A good starting point is to work with a trusted AI vendor such as MicroStrategy. Here at MicroStrategy, our combination of AI and business intelligence (BI) enables the use of natural language for data queries, dashboard creation, SQL generation, and online system help.

MicroStrategy AI builds on decades of BI expertise and industry-leading semantic graph to ensure transparency and accuracy. By developing a built-in semantic layer, we address all the concerns and make sure we use AI responsibly. To learn more about adding value for your enterprise from Gen AI, download your copy of the Forrester Research report “Generative AI Prompts Productivity, Imagination, and Innovation in the Enterprise”.