AGI in 2025? How Enterprise Leaders Should Prepare
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If artificial general intelligence (AGI) could arrive in 2025, enterprise teams have some work to do.
OpenAI Co-Founder and CEO Sam Altman casually predicted he’s “excited” for AGI in 2025 in a recent interview with Y Combinator. OpenAI defines AGI as “AI systems that are generally smarter than humans.”
Here, a group of AI leaders share how enterprises can get ready for AGI — and when they believe AGI may reach the market.
Looking to AGI
• How Should Executives Prepare for AGI?
How Should Executives Prepare for AGI?
AI leaders have a “unique responsibility to steer the conversation about AGI toward positive, human-centric outcomes,” said Robin Patra, head of data, platform, product and engineering at ARCO Construction.
“Our focus must shift from whether AGI will arrive to how we prepare society, businesses and governments to coexist with it,” Patra said. “This involves continuous innovation, governance and above all, collaboration across sectors.”
Implement and Use AI Now
Enterprises should always be prepared for change, despite differing opinions on AGI’s timing, said Raj Krishnan, a director at Microsoft.
Before considering AGI, organizations should focus on using AI “as it currently exists,” developing solid plans to move from pilot projects to successful deployments, Krishnan said. With a foundation, the lessons learned will “help prepare organizations for a future in which AGI can be used to build better, more powerful AI systems.”
AI leadership can prepare for AGI by “bringing today’s plans for AI to the next level,” by looking at “how they can take advantage of the upside of AI while protecting against the risks,” said Nicolas Chapados, VP of research at ServiceNow.
Corporate investments, he said, in data quality, AI infrastructure and integrations will “continue to pay off in an AGI world.”
Identify AGI Use Cases and Prepare Data
To prepare for AGI, AI leaders need to "define the context and use cases for AGI,” said Krishna Subramanian, co-founder and COO of Komprise.
For instance, she said, enterprises could start with generative AI for chat, as it’s a” great humanistic interface,” but the knowledge it uses comes from predictive AI or heuristic-based solutions.
In terms of data, AI leaders need to define how corporate data can interface with AGI, preparing how data will be searched, curated, ingested and audited for AI data workflows, which “will become critical,” Subramanian said.
Establish AI Governance
AI leaders must proactively establish governance models that “align with AGI's potential capabilities,” including defining ethical boundaries, legal compliance and decision-making frameworks, Patra said.
For example, during the AI transformation Patra helped lead at BlackRock, the team integrated ethical decision-making into investment algorithms to “ensure fairness and regulatory compliance.” AGI, he said, will “demand even more robust systems to manage its autonomous decision-making capabilities.”
The implementation of robust AI governance frameworks, including substantial investment in safety and security, will be critical to “limit downside risk” and ensure that AI’s rapid pace of development “remains aligned with the organization’s and society’s goals and values,” Chapados said.
Build Up Cybersecurity
AI leaders preparing for much more advanced AI need to “think about defense,” said Jason Stanley, head of the trust and governance lab at ServiceNow.
As AI capabilities improve, “they arm malicious actors outside organizations with sophisticated tools for attacks,” Stanley said. Leaders in AI need to understand, he said, where their organization is vulnerable, how threat vectors and attack types are evolving and what tools and skills they need to defend themselves.
“Even in cases where AI leaders decide to take a conservative posture on AI adoption internally, they won’t have a choice but to rework their defensive tools and posture, which might imply needing to adopt new AI for security technologies,” Stanley said.
Develop Human-Centric AI
Leaders in AI should prioritize designing AGI systems that “align with human values and needs,” Patra said. Human-centric AI, he said, requires embedding explainability, transparency and bias mitigation at the core of AGI development. Leaders should establish feedback loops where AGI systems are regularly “audited and adjusted” based on real-world use cases.
Upskill the Workforce
Enterprises need to prepare their workforce to “collaborate with AGI,” including upskilling teams to use AGI as a tool “rather than fearing it as a competitor,” Patra said.
In the construction industry, for instance, Patra’s seen how “AI can augment human capabilities,” improving safety and efficiency. AGI, he said, will “amplify this dynamic but only if the workforce is ready to adapt.”
Leadership “at all levels” should assess the organizational impact of AGI and invest in workforce development, Chapados said.
Instead of focusing on when AGI may arrive, AI leaders should focus on when AI systems are “getting close to or better than human performance on the task areas key to their business,” Stanley said.
“This could be much sooner than when we achieve overall AGI,” Stanley said.
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Will AGI Arrive in 2025?
Randall Hunt, CTO at Caylent, said “AGI isn't arriving in 2025.”
Krishnan with Microsoft said he’s “skeptical that AGI will arrive by 2025, unless we redefine and clarify what AGI truly entails and what significant changes we expect beyond current AI limitations.”
Patra at ARCO Construction said he’s skeptical, and “while the pace of AI advancements is staggering, AGI arriving by 2025 is highly ambitious.”