Bridge the chasm between business and IT with Writer’s AI HQ

Writer is reframing its platform as ‘AI HQ’ to close a fundamental disconnect that plagues enterprise AI: the gap between IT’s governance concerns and the business’ hunger for automation. Writer wants to be your choice for building, activating, and supervising enterprise-grade AI agents in a model for AI that business and IT could actually share.

The C-suite tug-of-war between IT and business is slowing progress

A recent HFS Market Impact Paper on AI progress in the enterprise identified the lack of mature joint IT-business leadership models as a significant strategic debt we must pay down to succeed with AI.

The C-suite AI tug-of-war between IT and business is leaving organizations directionless in their AI journey. AI is ultimately a business strategy enabled by emerging technology, but too many enterprises still assign their technology solutions, including emerging AI solutions, to the CIO’s organization to lead. In this vein, 44% of organizations still see IT as the primary AI leader, pulling from IT’s purse strings, with only a third achieving mature joint IT-business leadership models.

— HFS report ‘Only 12 percent of firms have cracked the AI maturity code’

Writer’s pivot brings collaborative agent design and the integration to make those designs work

The centerpiece of Writer’s shift is Agent Builder, now in public preview—a collaborative design environment where developers and business users can co-create AI agents that are tightly integrated into enterprise systems and grounded in business data.

Writer’s vision is bold: give both sides tools that suit their needs—a low-code/no-code canvas for business, and full SDKs and logic blocks for IT—enabling the two sides to collaborate where it counts. Its new ‘build, activate, supervise’ paradigm represents a rare vendor effort to structure the lifecycle of enterprise AI agents in a way that acknowledges both governance and speed.

Pre-built agents give you a head start—but not a strategy

As part of the AI HQ rollout, Writer has launched more than 100 ready-to-deploy agents, covering enterprise workflows in financial services, healthcare, retail, sales, customer support, and more. And there are different kinds of agents depending on the level of control, planning, and reasoning required of them.

You still need a structured framework for assessing agent applicability by risk and impact—such as the HFS A-G-E-N-T framework. The responsibility falls squarely on enterprise leaders to apply thoughtful governance before chasing scale. Writer offers services that support this, including self-paced training, deployment playbooks, and teams to assess AI maturity, train technical leaders, and measure business impact.

Supervision is maturing—with oversight concerns addressed

To support enterprise-scale deployment, Writer is also rolling out observability and supervision tools. These include real-time usage metrics, performance dashboards, step-level traces, and access control—all rapidly becoming table stakes for scaling safely across business units.

Governance will extend into reversibility, with versioning and rollback capabilities slated for upcoming releases. Self-evolving agents powered by Writer’s forthcoming innovation in self-evolving LLMs will include toggles to control how (and if) agents learn over time—addressing a critical concern for enterprise leaders when considering the oversight of autonomy.

What do you pay and who is going to buy?

The commercial model is also changing. Writer is moving to a dual offering—Starter and Enterprise plans—aimed at supporting mass-scale experimentation and build-outs. The Starter plan gives users immediate access to the entire platform, first with a free 14-day trial and then at $29 per month to use its 100-plus prebuilt agents and build up to 5 additional custom agents.

The balancing act of meeting both business and IT needs begs the question: whose budget is going to foot the bill? Appreciating the nuances of unlocking a joint IT-business budget will be critical to ensuring the success of AI HQ.

Leaders must lean in with clear-eyed discipline:

• Understand which use cases are right for what kind of agents—leading to lower risk opportunities.
• Insist on observability and plan for reversibility—before committing high-stakes processes to autonomous agents.
• Establish clear accountability between IT and business from day one—because collaboration on this platform cannot be optional.

Real customers, real traction—but don’t let the logos lull you

Writer points to live examples at Uber, Commvault, and Franklin Templeton to back its claims. The Franklin Templeton case is especially telling: using Writer agents to generate regulated market commentary and prepare Salesforce account briefings grounded in Snowflake data, SEC filings, and web search.

That said, buyer caution is still warranted. Success at one enterprise does not guarantee readiness for yours. Data security, integration maturity, and change management remain core differentiators—and risks—when deploying AI at this scale.

The Bottom Line: Writer has listened to enterprise concerns. Leaders must decide if all their questions have been answered.

Writer’s pivot to the agentic-led AI HQ platform represents a meaningful shift in the GenAI landscape and acknowledges important pain points: business-IT misalignment, governance gaps, and lack of scalable agent lifecycle management.

You must now decide if these are the answers you were seeking to drive your AI ambitions forward. If not, use Writer’s AI response to identify what more you need before taking the leap.