Maximising Productivity: How For-Profits are Successfully Implementing AI
"The future is already here—it's just not evenly distributed." When sci-fi author William Gibson coined this phrase decades ago, he couldn't have known how well it would describe today's AI landscape. While tech giants and Fortune 500 companies have deployed AI systems worthy of a Tony Stark workshop, many small organisations still view AI as something out of a sci-fi film—powerful but impractical for their everyday needs.
The reality? AI has crossed the threshold from futuristic fantasy to practical business tool, and small and medium-sized businesses are proving that you don't need Iron Man's budget to harness its power. These organisations are leveraging AI to drive significant improvements in efficiency, productivity, and overall operational excellence. As nonprofits consider their own AI readiness, they can learn from the successes (and occasional missteps) of their for-profit counterparts.
The AI Productivity Advantage: By the Numbers
Recent studies have confirmed that AI implementation delivers measurable productivity gains.
A 2023 Harvard-Wharton study found that Boston Consulting Group consultants using AI on average completed 12% more tasks, 25% faster and with a 40% increase in quality. Importantly, the productivity benefits were more significant for lower-skilled workers, suggesting AI's potential as an equalizing force
Researchers from Harvard and Wharton also found that P&G workers using AI showed a significant improvement in the quality of their work, with AI effectively replicating the performance benefits of having a human teammate. AI enabled individuals and teams to work 12-16% faster and helped bridge knowledge gaps, enabling amateurs to act more like experts. Interestingly, individuals working with AI had emotional experiences comparable to or better than those working in human teams.
For-profits using AI to improve productivity: case studies
Modernising internal operations and stakeholder management: House of Ponce, an interior design firm, was able to significantly streamline their projects using an AI solution. House of Ponce was struggling with inconsistent communication, fragmented documentation and excessive time spent on follow ups. Digs, a real estate-focused AI solution, enabled House of Ponce to have a single source of truth, with AI-powered search and smooth hand-offs between stakeholders. As a result, House of Ponce has saved 5-10 hours per week previously spent searching for documents and specifications, as well as preventing 3-5 errors per projectk. Stakeholders now access the latest updates independently, reducing delays and miscommunication.
Modernising internal operations and automating document drafting: A&O Shearman, a leading international law firm, used Harvey AI to modernise routine manual workflows like drafting, summarization, clause comparisons and precedent searches. As a result, staff save 2-3 hours per week on routine tasks like summarisation, analysis and translation; using generative AI for contract drafting and negotiation further cut their contract review time by 30%. Importantly, the AI system highlights its proposed edits, ensuring a human is always in the loop.
Streamlining financial processes: Higher Ground, a global Montessori school operator, had a complex invoice approval process. Higher Ground utilized vic.ai to delegate a majority of the invoice processing to AI and to simplify the approval process, resulting in a 60% improvement in invoice time.
Improving marketing workflows: Powers Law Group, a Texas immigration firm, was struggling with disorganisation - contacts scattered across different databases, different software systems, and no clear way to track leads. This disorganisation led to breakdown in workflows, struggles to reply to leads and missed opportunities to build trust with clients. Lawmatics, a legal-specific AI marketing platform, enabled the firm to automate lead intake and follow-up communications, track client interactions and measure the effectiveness of marketing campaigns. The result was an improved client conversion rate and improved revenue while saving significant time.
Implementation Path and Considerations
Are you a nonprofit thinking about how to improve your workflows? Consider this path:
Identify areas where AI can address specific business challenges. Focus on areas where AI can make your team’s life easier, e.g. on time-consuming or friction-filled processes.
Research AI solutions that align with your needs and budget. Some things to keep in mind:
Ensure AI systems comply with data privacy regulations like GDPR and protect sensitive information.
Be mindful of potential biases in AI algorithms - see more on ethical considerations for AI use by nonprofits in our post here.
AI platforms designed for specific industries may make more sense than attempting to customize general-purpose AI solutions
Start with a pilot project to test and evaluate the effectiveness of AI. Data quality is critical - companies that invested in having clean data and strong data infrastructure before implementation saw better results.
Train your staff on how to use and interact with AI systems. Recall that having a human-in-the-loop is critical for the most sensitive tasks. Companies that achieve the best results don’t position AI as a replacement for human workers, but as a tool to enhance their capabilities. Work on building AI literacy across the organization.
Continuously monitor and optimise AI performance to ensure ongoing success.
The AI revolution isn't just for large corporations or tech-focused organizations. Organizations across diverse sectors have demonstrated that strategic AI implementation—particularly with industry-specific platforms—can deliver significant operational improvements without a massive resource requirement. The key is finding AI solutions that understand your specific context.
