# Practical Innovation: How Operations Leaders See AI Adoption

> In the evolving landscape of AI, operations leaders are the AI realists. Here's how they can ensure their teams not only adopt AI but actively embrace it.

Source: https://asana.com/resources/state-of-ai-operations

## Practical innovation: How operations leaders see AI adoption

As technology evolves and AI creates new ways to innovate and streamline work, operations professionals find themselves at a crossroads. AI isn’t just a concept—it’s changing how organizations work, right here, right now. But there are two sides to the coin. While AI presents unprecedented opportunities, it also comes with challenges. 

To better understand the current landscape and mindset surrounding AI, [The Work Innovation Lab](https://asana.com/work-innovation-lab), a think tank by Asana, conducted a study of over 4,500 individual contributors, middle and senior managers, and executives in the U.S. and U.K  The narrative that emerged was clear: operations leaders are approaching AI with a mixture of optimism and practicality. While they recognize that AI holds immense promise, they also acknowledge the complexities that come with integrating and adopting the technology. 

#### The Work Innovation Lab とは？

AI を活用したオートメーションやエージェンティック AI から、ソーシャルコマースやマイクロコミュニティまで、2026年に影響を与える主要なマーケティングトレンドをご紹介します。 プライバシー重視の世界において、カスタマーエクスペリエンスを向上させ、ブランドとの本物のつながりを築き、成功度を測定する方法をご説明します。
- [調査レポートを見る](/work-innovation-lab)To be successful, operations leaders must balance AI’s revolutionary potential with possible concerns—and ensure their organizations don’t just adopt AI, but do so responsibly, effectively, and with an eye toward long-term growth. Continue reading to uncover the insights The Work Innovation Lab gleaned from operations professionals regarding the expanding role of AI in operations. Plus, discover practical strategies you can adopt to realize the full potential of AI in your organization.

#### An operator's playbook for powering your organization with AI

Leverage AI to amplify human potential and drive organizational success. Download our AI playbook, designed specifically for operations professionals, for actionable insights on how to use AI in operations—including how to build a unified AI strategy.
- [Get the insights](/resources/human-centric-ai-operations-playbook)
- [Get the insights](/resources/human-centric-ai-operations-playbook)

## Operations leaders are AI realists

When it comes to AI adoption, operations leaders have positioned themselves as practical innovators. Research from The Work Innovation Lab revealed that while 50% of operations professionals foresee AI playing a role in goal-setting and 55% believe AI can help achieve objectives more effectively than traditional methods, 63% doubt AI's ability to boost productivity—and fear it might even reduce it. What’s more, only 31% of operations professionals anticipate their companies investing in AI in the coming quarter. 

This duality suggests that operations teams are going to have to perform a challenging balancing act. At its core, successful AI adoption hinges on open conversation, custom-tailored training, and a culture of continuous learning. By acknowledging workers’ concerns and championing AI’s advantages, operations leaders can make sure their teams not only adopt AI but actively embrace it. 

## How to steer success: 6 actionable strategies for driving AI adoption

Many operations leaders are grappling with how to effectively incorporate AI into their work and drive real results. Here are six key takeaways from the study: 
- **Advocate for AI-specific operations training.**Only 16% of operations professionals feel they’ve received AI training that’s relevant to their job, showing a clear need for organizations to invest in training that’s tailored to their needs. Operations leaders should champion specialized AI training that addresses unique challenges and opportunities for their teams. 
- **Focus on human-centric AI applications.**Highlight the collaborative role of humans and AI by focusing on AI initiatives that complement human capabilities—like those that use AI to help with decision-making, automate repetitive tasks, and provide actionable insights to free up time for high-value, uniquely human work.
- **Establish clear AI guidelines and emphasize transparency.**Build trust among employees—and ensure AI is used responsibly—by advocating for clear policies and procedures that govern the use of AI in your organization’s operational processes. 
- **Address AI concerns head-on to foster optimism.**The Work Innovation Lab’s study found that executives are leading the charge in AI adoption and optimism, but the broader workforce is trailing behind. Establish channels for employees to provide feedback on AI initiatives and champion the technology as a positive change to bridge this gap. 
- **Take tangible steps to reinforce your commitment to AI.**Demonstrate your dedication by actively investing in AI initiatives, such as spearheading AI pilot projects, setting aside dedicated AI funds, and providing AI training and support to employees. 
- **Celebrate AI wins and foster a culture of learning.**Highlight AI’s force for positive change by encouraging employees to experiment with AI technology, creating methods for sharing feedback and inspiration, and spotlighting employee stories of success and innovation.

## Dig deeper

Eager for more insights? Download the full playbook for more actionable strategies you can put into practice in your organization. Learn how to navigate the gaps in AI perception between leaders and individual contributors, gain guidance to strategically select AI vendors, and learn the meaning of “human-centric” AI.

AI の現状

- [AI 導入で変わる意思決定プロセス: 経営戦略と現場を同期させる次世代のガバナンス](/ja/resources/ai-decision-making-process)

AI の現状

#### コンテンツライター

AI による意思決定とはAI による意思決定とは、人工知能が膨大なデータから最適解を導き出し、人間の判断力を高度に拡張するプロセスです。その根幹にあるのは、経験や主観ではなく客観的な数値を拠り所とするデータ駆動型 (データドリブン) 経営です。変化の激しいビジネス環境において、経営層は市場動向や財務データを可視化することでリスク管理に基づいた迅速な判断を行 ...

- [自治体 AI 導入完全ガイド 2026: 官公庁の最新活用事例と行政 DX を成功させる 5 つのステップ](/ja/resources/public-sector-ai-adoption)

AI

#### コンテンツライター

自治体、行政における AI 導入の現状と背景現在、日本の多くの自治体の現場では、多様化する住民ニーズへの対応や深刻な労働力不足という大きな課題に直面しています。この課題解決の切り札として、人工知能、とりわけ生成 AI の活用が急速に広がっています。総務省の調査や各地の報告によれば、自治体における生成 AI の利用は、もはや一部の先進的な取り組みにとどまらず ...

- [中小企業のための AI 活用例 18 選｜補助金や事例、アイディア](/ja/resources/smes-ai-applications)

AI の現状

#### コンテンツライター

中小企業こそ AI を戦略的に導入することで、競争力の強化と持続的な成長を実現できます。本記事では、中小企業がどのように AI の活用を進め、DX (デジタルトランスフォーメーション) を実現できるのか、具体的な活用事例も交えながら解説します。中小企業にとって AI が不可欠な理由2030 年問題や 2050 年問題で代表されるように、深刻な人手不足の時代 ...

- [自治体における AI データ分析実践ガイド: 業務効率化へのステップと成功事例](/ja/resources/local-gov-ai-data-analysis-guide)

AI の現状

現代の地方自治体が直面する人手不足と財政の壁。これらの課題を乗り越え、持続可能な行政サービスを実現するためには、データ駆動型行政への転換が不可欠です。膨大な行政データから真の価値を引き出し、具体的な業務効率化と住民サービス向上へとつなげるための「AI データ分析の実践ガイド」をご覧ください。はじめに: データ駆動型行政への転換現在、日本の地方自治体は「AI ...

- [Practical innovation: How operations leaders see AI adoption](/ja/resources/state-of-ai-operations)

AI の現状

AI の現状

- [コンテンツライター](/author/whitney-vige)

As technology evolves and AI creates new ways to innovate and streamline work, operations professionals find themselves at a crossroads. AI isn’t just a concept—it’s changing how ...
