"What to Watch in AI: From Knowledge Search to Governance Controls"

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Hatched by Glasp

Aug 07, 2023

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"What to Watch in AI: From Knowledge Search to Governance Controls"

The exponential rise in "knowledge" and the increasingly distributed nature of work have significantly impacted the way we find and access information within organizations. The process of "searching for stuff" at work has become fairly broken, resulting in a waste of time and decreased productivity. As companies become more dispersed and knowledge becomes more fragmented, the need for an intuitive work assistant like Glean has transitioned from a nice-to-have feature to a critical tool in driving employee efficiency.

However, even with the growing importance of AI applications in the workplace, many enterprises face a major hurdle in shipping these applications to production – the lack of appropriate governance controls. Ensuring that AI applications understand what the end user is allowed to see and not see, determining where the inference is done, and identifying the source data that led to a given model output and its ownership are significant challenges. Without proper governance controls, enterprises run the risk of compromising sensitive information or violating privacy regulations.

Moreover, data processing and annotation remain the most tedious and expensive part of the AI process, yet they are also the most crucial for achieving high-quality outcomes. While pre-trained large language models like GPT-4 have gained popularity, enterprises must not overlook the significance of leveraging their proprietary data across various modalities. By utilizing their own data, organizations can create production AI models that lead to differentiated services, valuable insights, and increased operational efficiencies.

In the realm of cost management, avoidable costs play a vital role in determining a company's financial health. An avoidable cost refers to an expense that can be eliminated if a specific activity is not performed. Typically, avoidable costs are variable costs that can be removed from a business operation, unlike fixed costs that must be paid regardless of the company's activity level. By identifying and eliminating avoidable costs, businesses can improve their profitability and streamline their operations.

For instance, a company with multiple product lines can choose to exit underperforming ones, thereby eliminating the costs associated with them. This strategic decision allows the company to focus its resources on more profitable ventures. However, it's essential to note that while variable costs are theoretically avoidable, they may not be entirely eliminated in a short timeframe. This is because the company may still be bound by contracts with workers for direct labor or with suppliers for direct materials. Once these agreements expire, the company gains the freedom to drop these costs fully.

To navigate the challenges related to AI and avoidable costs effectively, here are three actionable pieces of advice:

  • 1. Prioritize Governance: Implement robust governance controls and ensure that your AI applications understand and adhere to the rules and regulations pertaining to data privacy and user access. This will not only protect sensitive information but also build trust with customers and stakeholders.
  • 2. Invest in Data Processing: While pre-trained models offer convenience, focus on utilizing your own proprietary data to create AI models that provide unique insights and deliver differentiated services. Investing in data processing and annotation will yield higher-quality outcomes and enable you to leverage your competitive advantage.
  • 3. Regularly Assess and Eliminate Avoidable Costs: Conduct regular cost assessments to identify avoidable expenses within your operations. Make strategic decisions to exit underperforming product lines or renegotiate contracts to eliminate unnecessary variable costs. This will help optimize your cost structure and improve overall profitability.

In conclusion, as AI continues to shape the future of work, organizations must pay attention to key aspects such as knowledge search, governance controls, proprietary data utilization, and avoidable costs. By addressing these areas effectively, businesses can enhance productivity, achieve cost savings, and stay ahead in the competitive landscape. Embracing AI technologies while maintaining a strategic focus on cost management will pave the way for success in the digital era.

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