A practical guide to managing AI risks in the workplace.
Do’s & Don’ts for smart use of AI in the workplace.
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Risk
Privacy
Access
Trust
Innovate
Manage Costs
Manage Costs
Security
Transparency
Do’s
Understand the T&Cs of AI services to ensure data privacy.
Implement your own AI via API for tasks requiring confidential data.
Adopt single-sign-on (SSO) to ensure controlled AI access.
Maintain regular access audits to keep track of AI users.
Critically assess AI-produced content like any human output.
Continually validate AI insights with domain experts.
Encourage your staff to explore AI as part of their normal work using approved AI services.
Dont’s
Enter confidential data into public AI platforms, even within paid tiers.
Use confidential data to train public AI platforms.
Use personal accounts for business purposes.
Give unrestricted access without proper review.
Blindly trust AI outputs solely based on polished presentation.
Rely solely on AI without human validation, especially for critical tasks.
Foster a culture of AI exploration within approved boundaries.
Invest in AI upskilling programs for staff.
Monitor AI-associated costs to avoid overpaying for redundant services.
Allocate a specific budget for AI R&D to assess new tools and services.
Foster a culture of AI exploration within approved boundaries.
Invest in AI upskilling programs for staff.
Ensure AI tools comply with industry-specific security standards.
Maintain up-to-date encryption and security protocols for data used in AI.
Educate stakeholders about how AI decisions are made within your organization.
Maintain a clear AI ethics guideline and ensure it's regularly updated.
Assume AI will solely replace human roles.
Resist adopting AI due to unfamiliarity or perceived lack of immediate ROI.
Assume all AI services will yield positive ROI.
Dive into every new AI tool without a clear cost-benefit analysis.
Assume all AI services will yield positive ROI.
Dive into every new AI tool without a clear cost-benefit analysis.
Neglect regular security assessments of your AI tools.
Overlook potential security vulnerabilities while focusing on AI features.
Keep AI operations as a 'black box' without explaining to relevant parties.
Ignore potential ethical dilemmas posed by AI decisions.
Responsible AI Framework
Auror's Responsible Tech & AI framework and documents help advance the safe and responsible use of AI. They have made their framework available to all for free.
Do you need a Chief AI Officer?
An AI-first approach implies that a company's strategies, culture, and operations are centered around leveraging AI across all business areas. The Chief AI Officer is integral to directing a company toward becoming AI-first. Here's how:
Strategic Leadership
The CAIO develops an AI roadmap and strategy that weaves AI into the core fabric of the business, ensuring that AI isn't just an added feature but is central to problem-solving and innovation.
Advocacy
The CAIO champions AI internally and externally, advocating for its use to stakeholders, partners, and clients. They drive adoption by highlighting success stories and illustrating the transformative potential of AI.
Cultural Transformation
The CAIO works to foster an AI-positive culture within the organisation. This involves training and educating staff about AI, promoting its benefits, and encouraging a mindset of continuously looking for opportunities to implement AI solutions.
Ethics and Compliance Oversight
The CAIO ensures that AI is used responsibly and ethically, helping build trust in AI systems within the company and with its customers.
Cross-Functional Collaboration
To truly become AI-first, AI integration has to occur across all business functions. The CAIO collaborates with different departments to identify opportunities for AI integration and improve existing processes.
Keeping Pace with AI Development
The AI landscape is continually evolving. A CAIO must stay updated on the latest developments, helping the company adapt and integrate emerging AI technologies effectively.