deutsche telekom

An opportunity to position the ready-to-launch AI Phone as a true collaborative partner for users, helping to achieve product-market fit.

Domain

Consumer Technology + Telecommunications

STATUS

Proof of Concept (POC)

UNDERTAKEN AT

Deutsche Telekom + Politecnico di Milano

Overview

Deutsche Telekom is a leading European telecommunications provider, renowned for its digital innovation and expansive network services.


In a strategic move to enter the smartphone market, Deutsche Telekom launched an AI phone that reimagines what a mobile device can do by embedding Magenta AI (Deutsche Telekom's proprietary AI) at the core of the experience.

final deliverable

Finding product-market fit by making Magenta AI a true thinking partner, not just delegate to it.

Our primary goal was to find product-market fit for Deutsche Telekom as it entered the AI phone market. We wanted to go beyond creating just another smart device; instead, we focused on designing Magenta AI (Deutsche Telekom's intelligent assistant platform in collaboration with Perplexity) around the concept of "thinking with AI."


This meant making the AI not just a passive assistant or autopilot, but an active thinking partner. Someone users could collaborate with to navigate information overload, make smarter decisions, and bring more meaning and balance into their digital lives.


By emphasizing AI as a cognitive copilot, we aimed to address the fragmented experiences and trust issues that users face with current digital tools.

our driver

How can AI become a true collaborator, fostering trust, balance, and meaningful engagement rather than adding complexity?

How can AI become a true collaborator, fostering trust, balance, and meaningful engagement rather than adding complexity?

Secondary Research

How did we establish a foundation of understanding through secondary research methodologies?

The research methodology combined blue sky research with comprehensive market trend analysis, following established principles of exploratory, curiosity-driven investigation.


Blue sky research, defined as "research without a clear goal" that focuses on fundamental understanding rather than immediate applications, provided the conceptual foundation for exploring AI's role in human cognition.

Blue Sky Research Findings

Literary Analysis


Examined speculative AI narratives from "Snow Crash" by Neal Stephenson and "Atlas of AI" by Kate Crawford, exploring AI as embedded agents and co-pilots.


Product Ecosystem Study


Analyzed existing AI implementations including Google's Smart Reply predictive text, Detroit: Become Human's adaptive responses, and Nest Thermostat's behavioral pattern recognition.


Cognitive Science Integration


Investigated key forms of human thinking (critical, creative, analytical, divergent, logical, practical) and their intersection with AI capabilities.

Market Research and Trends Analysis

Generative AI Market Growth


Market size projected to reach $442.07 billion by 2031, representing explosive growth from $7.69 billion in 2021.


AI Usage Typologies


Identified distinct AI categories (Small Language Models, Multimodal, Agentic) serving different user interaction needs.


Business Adoption Drivers


75% of knowledge workers using AI tools, with primary applications in eliminating repetitive tasks and improving efficiency.

What critical market insights shaped our design direction?

Consumer AI Adoption


60% of consumers consider AI features important when choosing smartphones, with 21% labeling them "very important"


Upgrade Acceleration


AI features driving faster device replacement cycles, with average trade-in age decreasing significantly


Market Polarization


Growing demand for both entry-level AI-enabled devices and premium AI-powered experiences

Primary Research

How did we validate our hypotheses through human-centered design investigation?

The team conducted comprehensive primary research with 20 participants aged between 20 to 60. This research followed human-centered design principles, focusing on empathy-building and need identification.

Investigation covered five critical areas

  1. Cognitive Load & Pain Points in Thinking

  2. Current Strategies for Managing Mental Load

  3. Outsourcing Thinking & Decision-Making

  4. Usage & Trust in AI for Cognitive Tasks

  5. Expectations and Desires for AI Support

What compelling behavioural patterns emerged?

75%


use writing tasks (physical notes or apps) as their main method of organizing thoughts

75%


use writing

tasks (physical notes or apps) as their main method of organizing thoughts

55%


would accept integrated AI if it simplifies life

55%


actively delegate tasks to people or technology

55%


actively

delegate tasks to people or technology

70%


feel overwhelmed by too many choices at once

70%


feel over whelmed by too many choices at once

35%


desire AI that can grasp emotional context

35%


desire AI that can grasp emotional context

65%


use AI for research, summaries, or idea generation, but only 15% trust AI for final decisions

Opportunity Area

Which strategic opportunity areas emerged from our research synthesis?

Hybrid Thinking

Supporting combined human-AI cognitive approaches

AI and Cognitive Balance

Balancing between AI assistance and human agency

Evaluating Alternatives

Helping users navigate complex decision spaces

Segmented Thinking & Personalization

Adapting to individual cognitive styles

Adapting to individual cognitive

styles

Visibility in

Data Usage

Ensuring transparency in AI decision-making processes

Trust and Transparency

Building reliable, explainable AI systems

Natural Interaction

Enabling intuitive human-AI communication

Contextual

Intelligent Memory

Creating AI that understands and remembers context

Key moments with Deutsche Telekom and Politecnico di Milano.

conceptual use cases

We translated the opportunity areas into concrete product concepts.

USE CASE 1

Parallea – The Mind’s Multitasking Ally

For individuals juggling a demanding blend of work, home, and personal commitments, Parallea serves as an intelligent, unified cognitive assistant that streamlines fragmented daily tasks.


By proactively organizing reminders, facilitating natural delegation, and maintaining contextual memory, the system reduces mental overload and helps users seamlessly transition between roles, creating calm and reliable support for a complex, multitasking lifestyle.

USE CASE 2

EchoRoom – Collaborative Decision Space

Empowers groups sharing responsibilities such as large project teams to collaborate productively by centralizing coordination, expense tracking, and real-time communication.


With AI-driven conflict detection, group polling, and transparent scheduling, the experience fosters fairness, enabling smoother collective decision-making and reducing misunderstandings in dynamic, multi-user environments.

USE CASE 3

AgileMind – Interconnected Collaborative Canvas

Supports those balancing professional, academic, and social spheres by connecting physical and digital workflows into one cohesive, intelligent platform.


Acting as a partner in brainstorming, research, and planning, it bridges handwritten and digital thinking, prompts reflective insights, and coordinates group discussions—helping users maintain focus, manage emotional stress, and stay aligned across multiple domains.

future Strategy

What strategic implementation approach would ensure successful market entry?

PHASE 1

Research & Foundations

If we were building this for full-scale implementation, we would spend even more time immersing ourselves in the diverse realities of our potential users.


We’d extend our research beyond initial interviews to include longitudinal ethnographic studies, shadowing individuals as they navigate their daily thinking patterns and tool usage. By bolstering ethical benchmarks and user journey mapping, we’d ensure every insight truly reflected lived experiences and evolving needs.

PHASE 2

UX & Interaction Design

With additional time, we would invest deeply in iterative prototyping and co-design workshops, inviting users to shape not just the interface but also the AI’s personality and mannerisms.


We’d rigorously test conversation flows, decision-making tools, and consensus-building features across varied contexts—refining until interactions felt both natural and trustworthy at every touchpoint. Advanced user testing would let us perfect accessibility, emotional nuance, and cross-device intelligence.

PHASE 3

System & Platform Integration

Given a real-world runway, we’d work to integrate the AI seamlessly with a broad ecosystem, bridging calendars, messaging, notes, smart home devices, and even wearables.


We’d collaborate with data privacy experts to build a robust, user-controlled permission framework, ensuring absolute transparency and trust. Continuous feedback loops and analytics would guide ongoing improvements, cementing the solution as an indispensable daily companion across all facets of life.

Learnings

Key takeaways.

Working with the AI Phone allowed us to wear to multiple hats, it also demonstrates the successful application of comprehensive research methodologies, user-centered design thinking, and strategic market positioning to create innovative AI-powered solutions.

designed and built with šŸ’™ by ashish konkankar Ā© 2025.

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designed and built with šŸ’™ by a

shish konkankar Ā© 2025.

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